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COMPUTATIONAL
SYSTEMS BIOLOGY
SECOND EDITION
COMPUTATIONAL
SYSTEMS BIOLOGY
SECOND EDITION
Edited by

Roland Eils
Andres Kriete

AMSTERDAM • BOSTON • HEIDELBERG • LONDON

NEW YORK • OXFORD • PARIS • SAN DIEGO
SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO
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Library of Congress Cataloging-in-Publication Data
Computational systems biology (Kriete)
Computational systems biology / edited by Andres Kriete, Roland Eils. -- Second edition.
   p. ; cm.
Includes bibliographical references and indexes.
ISBN 978-0-12-405926-9 (alk. paper)
I. Kriete, Andres, editor of compilation. II. Eils, Roland, editor of compilation. III. Title.
[DNLM: 1. Computational Biology. 2. Systems Biology. QU 26.5]
QH324.2
570.1’13--dc23
2013045039
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A catalogue record for this book is available from the British Library.
ISBN: 978-0-12-405926-9

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14 15 10 9 8 7 6 5 4 3 2 1
 Contributors

Chapter 1 Frédéric Crémazy Department of Synthetic

Roland Eils Division of Theoretical Bio­ Systems Biology and Nuclear Organization,
informatics (B080), German Cancer Research Swammerdam Institute for Life Sciences,
Center (DKFZ), Heidelberg, Germany University of Amsterdam, Amsterdam, The
Department for Bioinformatics and Func­ Netherlands
tional Genomics, Institute for Pharmacy Matteo Barberis Department of Synthetic Systems
and Molecular Biotechnology (IPMB) Biology and Nuclear Organization, Swam­
and BioQuant, Heidelberg University, merdam Institute for Life Sciences, University
Heidelberg, Germany of Amsterdam, Amsterdam, The Netherlands
Andres Kriete School of Biomedical Engineering,
Science and Health Systems, Drexel University, Chapter 4
Philadelphia, PA, USA Ursula Klingmüller, Marcel Schilling, Sonja
Depner, Lorenza A. D’Alessandro Division
Chapter 2 Systems Biology of Signal Transduction,
Robert B. Russell, Gordana Apic, Olga Kalinina, German Cancer Research Center (DKFZ),
Leonardo Trabuco, Matthew J. Betts, Qianhao Heidelberg, Germany
Lu CellNetworks, University of Heidelberg,
Heidelberg, Germany Chapter 5
Christina Kiel EMBL/CRG Systems Biology
Chapter 3 Re­search Unit, Centre for Genomic Regulation
Hans V. Westerhoff Department of Synthetic (CRG), Barcelona, Spain
Systems Biology and Nuclear Organization, Universitat Pompeu Fabra (UPF), Barcelona, Spain
Swammerdam Institute for Life Sciences, Luis Serrano EMBL/CRG Systems Biology Re­ ­
University of Amsterdam, Amsterdam, The search Unit, Centre for Genomic Regulation
Netherlands (CRG), Barcelona, Spain
Department of Molecular Cell Physiology, Faculty Universitat Pompeu Fabra (UPF), Barcelona, Spain
of Earth and Life Sciences, VU University ICREA, Barcelona, Spain
Amsterdam, The Netherlands
Manchester Centre for Integrative Systems Bio­ Chapter 6
logy (MCISB), Manchester, UK Seiya Imoto Human Genome Center, Institute
Fei He Manchester Centre for Integrative Systems of Medical Science, The University of Tokyo,
Biology (MCISB), Manchester, UK Minatoku, Tokyo, Japan
Department of Automatic Control and systems Hiroshi Matsuno Faculty of Science, Yamaguchi
Engineering, The University of Sheffield, University, Yoshida, Yamaguchi, Japan
Sheffield, UK Satoru Miyano Human Genome Center, Insti­
Ettore Murabito Manchester Centre for Integrative tute of Medical Science, The University of
Systems Biology (MCISB), Manchester, UK Tokyo, Minatoku, Tokyo, Japan

ix
x CONTRIBUTORS

Chapter 7 Chapter 11
Hong-Wu Ma Tianjin Institute of Industrial Bio­ Reinhard Laubenbacher Virginia Bioinformatics
technology, Chinese Academy of Sciences, Institute, Virginia Tech, Blacksburg VA, USA
Tianjin, P.R. China Pedro Mendes Virginia Bioinformatics Institute,
School of Informatics, University of Edinburgh, Virginia Tech, Blacksburg VA, USA
Edinburgh, UK School of Computer Science, The University of
An-Ping Zeng Institute of Bioprocess and Bio­ Manchester, Manchester, UK
systems Engineering, Hamburg University of
Technology, Denickestrasse, Germany
Chapter 12
Joseph Xu Zhou, Xiaojie Qiu, Aymeric Fouquier
Chapter 8
d’Herouel, Sui Huang Institute for Systems
Stanley Gu Department of Bioengineering, Uni­
Biology, Seattle, WA, USA
versity of Washington, Seattle, WA, USA
Herbert Sauro Department of Bioengineering,
University of Washington, Seattle, WA, USA Chapter 13
John Cole, Mike J. Hallock, Piyush Labhsetwar,
Chapter 9 Joseph R. Peterson, John E. Stone, Zaida
Juergen Eils Division of Theoretical Bioinformat Luthey-Schulten University of Illinois at
ics, German Cancer Research Center (DKFZ), Urbana-Champaign, USA
Heidelberg, Germany
Elena Herzog Division of Theoretical Bioinformat­
ics, German Cancer Research Center (DKFZ), Chapter 14
Heidelberg, Germany Jean-Luc Bouchot Department of Mathematics,
Baerbel Felder Division of Theoretical Bioinforma­ Drexel University, PA, Philadelphia, USA
tics, German Cancer Research Center (DKFZ), William L. Trimble Institute for Genomics and
Heidelberg, Germany Systems Biology, Argonne National Laboratory,
Department for Bioin­ formatics and Functional University of Chicago, Chicago, IL, USA
Genomics, Institute for Pharmacy and Gregory Ditzler Department of Electrical and
Molecular Biotechnology (IPMB) and BioQuant, Computer Engineering, Drexel University,
Heidelberg University, Heidelberg, Germany PA, Philadelphia, USA
Christian Lawerenz Division of Theoretical Bio­ Yemin Lan School of Biomedical Engineering,
informatics, German Cancer Research Center Science and Health, Drexel University, PA,
(DKFZ), Heidelberg, Germany Philadelphia, USA
Roland Eils Division of Theoretical Bioinformat
Steve Essinger Department of Electrical and Com­
ics, German Cancer Research Center (DKFZ),
puter Engineering, Drexel University, PA,
Heidelberg, Germany
Philadelphia, USA
Department for Bioinformatics and Functional
Genomics, Institute for Pharmacy and Molec­ Gail Rosen Department of Electrical and Com­
ular Biotechnology (IPMB) and BioQuant, puter Engineering, Drexel University, PA,
Heidelberg University, Heidelberg, Germany Philadelphia, USA

Chapter 10 Chapter 15
Jean-Christophe Leloup, Didier Gonze, Albert Helder I Nakaya Department of Pathology,
Goldbeter Unité de Chronobiologie théorique, Emory University, Atlanta, GA, USA
Faculté des Sciences, Université Libre de Bru­ Vaccine Research Center, Emory University,
xelles, Campus Plaine, Brussels, Belgium Atlanta, GA, USA

x
 xi CONTRIBUTORS

Department of Clinical Analyses and Toxicology, Chapter 18

University of Sao Paulo, Sao Paulo, SP, Brazil Hang Chang, Gerald V. Fontenay, Cemal Bilgin,
Bahram Parvin Life Sciences Division, Law­
rence Berkeley National Laboratory, Berkeley,
Chapter 16 CA, USA
Julien Delile Institut des Systèmes Complexes Alexander Borowsky Center for Comparative
Paris Ile-de-France (ISC-PIF), CNRS, Paris, Medicine, University of California, Davis, CA,
France USA.
Neurobiology and Development Lab, Terrasse, Paul Spellman Department of Biomedical Engi­
Gif-sur-Yvette Cedex, France neering, Oregon Health Sciences Univer­sity,
Portland, Oregon, USA
René Doursat Institut des Systèmes Com­
plexes Paris Ile-de-France (ISC-PIF),
Chapter 19
CNRS, Paris, France
Stefan M. Kallenberger Department for Bio­
School of Biomedical Engineering, Drexel Uni­
informatics and Functional Genomics, Divi­
versity, Philadelphia, PA, USA
sion of Theoretical Bioinformatics, German
Nadine Peyriéras Neurobiology and Develop­ Cancer Research Center (DKFZ), Institute for
ment Lab, Terrasse, Gif-sur-Yvette Cedex, Pharmacy and Molecular Biotechnology
France (IPMB) and BioQuant, Heidelberg University,
Heidelberg, Germany
Stefan Legewie Institute of Molecular Biology,
Chapter 17 Mainz, Germany
Andres Kriete School of Biomedical Engineering, Roland Eils Department for Bioinformatics and
Science and Health Systems, Drexel Univer­ Functional Genomics, Division of Theoretical
sity, Bossone Research Center, Philadelphia, Bioinformatics, German Cancer Research
PA, USA Center (DKFZ), Institute for Pharmacy and
Mathieu Cloutier GERAD and Department of Molecular Biotechnology (IPMB) and Bio­
Chemical Engineering, Ecole Polytechnique Quant, Heidelberg University, Heidelberg,
de Montreal, Montreal, QC, Canada Germany

xi
 Preface

Computational systems biology, a term coined in this area. If compared to the first edition
by Kitano in 2002, is a field that aims at a published in 2005, the second edition has been
­system-level understanding by modeling and specifically extended to reflect new frontiers of
analyzing biological data using computation. systems biology, including modeling of whole
It is increasingly recognized that living ­system cells, studies of embryonic development, the
cannot be understood by studying individual immune systems, as well as aging and cancer.
parts, while the list of molecular components As in the previous edition, basics of informa-
in biology is ever growing, accelerated by tion and data integration technologies,
genome sequencing and high-throughput ­standards, modeling of gene, signaling and
omics techniques. Under the guiding vision of metabolic networks remain comprehensively
systems biology, sophisticated computational covered. Contributions have been selected
methods help to study the interconnection of and compiled to introduce the different meth-
parts in order to unravel complex and net- ods, including methods dissecting biological
worked biological phenomena, from protein complexity, modeling of dynamical proper-
interactions, pathways, networks, to whole ties, and biocomputational perspectives.
cells and multicellular complexes. Rather Beside the primary authors and their
than performing experimental observations respective teams who have dedicated their
alone, systems biology generates knowledge time to contribute to this book, the editors
and understanding by entering a cycle of would like to thank numerous reviewers of
model construction, quantitative simulations, individual chapters, but in particular Jan
and experimental validation of model predic- Eufinger for support of the editorial work.
tions, whereby a formal reasoning becomes It is often mentioned that biological sys-
key. This requires a collaborative input of tems in its entirety present more than a sum
experimental and theoretical biologists work- of its parts. To this extent, we hope that the
ing together with system analysts, computer chapters selected for this book not only give
scientists, mathematicians, bioengineers, a contemporary and comprehensive over-
physicists, as well as physicians to contend look about the recent developments, but that
creatively with the hierarchical and nonlinear this volume advances the field and encour-
nature of cellular systems. ages new strategies, interdisciplinary coop-
This book has a distinct focus on computa- eration, and research activities.
tional and engineering methods related to sys-
tems biology. As such, it presents a timely,
multi-authored compendium representing Roland Eils and Andres Kriete
state-of-the-art computational technologies, Heidelberg and Philadelphia,
standards, concepts, and methods developed September 2013

xiii
 C H A P T E R

1
Introducing Computational
Systems Biology
Roland Eilsa,b, Andres Krietec
a
Division of Theoretical Bioinformatics (B080), German Cancer Research
Center (DKFZ), Heidelberg, Germany
b
Department for Bioinformatics and Functional Genomics, Institute for
Pharmacy and Molecular Biotechnology (IPMB) and BioQuant, Heidelberg
University, Heidelberg, Germany
c
School of Biomedical Engineering, Science and Health Systems,
Drexel University, Philadelphia, PA, USA

C O N T E N T S

1 Prologue 1 3 Outlook 6
2 Overview of the content 4 References 7

We need to turn data into knowledge and we need a framework to do so. S. Brenner, 2002.

1 PROLOGUE

The multitude of the computational tools needed for systems biology r­ esearch can roughly
be classified into two categories: system identification and behavior analysis (Kitano 2001). In
molecular biology, system identification amounts to identifying the regulatory relation-
ships between genes, proteins, and small molecules, as well as their inherent dynamics hid-
den in the specific kinetic and binding parameters. System identification is arguably one of
the most complicated problems in science. While behavior analysis is solely performed on
a model, model construction is a process tightly connected to reality but part of an iterative
process between data analysis, simulation, and experimental validation (Figure 1.1). A typical

Computational Systems Biology, Second Edition 1 © 2014 Elsevier Inc. All rights reserved.
http://dx.doi.org/10.1016/B978-0-12-405926-9.00001-0
2 1. Introducing Computational Systems Biology

FIGURE 1.1 Key to systems biology is an iterative cycle of experimentation, model building, simulation and
validation.

modeling cycle begins with a reductionist approach, creating the simplest possible model. The
modeling process generates an understanding of the underlying structures, and components
are represented graphically with increasing level of formalization, until they can be converted
into a mathematical representation. The minimal model then grows in complexity, driven by
new hypotheses that may not have been apparent from the phenomenological descriptions.
Then, an experiment is designed using the biological system to test whether the model predic-
tions agree with the experimental observations of the system behavior. The constitutive model
parameters may be measured directly or may be inferred during this validation process, how-
ever, the propagation of errors through these parameters present significant challenges for the
modeler. If data and predictions agree, a new experiment is designed and performed. This pro-
cess continues until sufficient experimental evidence in favor of the model is collected. Once
the system has been identified and a model constructed, the system behavior can be studied,
for instance, by numerical integration or sensitivity analysis against external perturbations.
Although the iterative process is well defined, the amount of data to be merged into this
process can be immense. The human genome project is one of the hallmarks indicating a turn
from a reductionistic approach in studying biological systems at increasing level, into a dis-
covery process using high-throughput techniques (Figure 1.2). Ongoing research increases the
wealth of contemporary biological information residing in some thousand public databases
providing descriptive genomics, proteomics and enzyme information, gene expression, gene
variants and gene ontologies. Refined explorative tools, such as new deep sequencing, along
with the emergence of new specialized -omics (metabolomics, lipidomics, pharmacogenom-
ics) and phenotyping techniques, constantly feed into this data pool and accelerate its growth.
Given the enormous and heterogeneous amount of data, computational tools have become
indispensable to mine, analyze, and connect such information. The aggregate of statistical
 1 Prologue 3

FIGURE 1.2 By the evolution of scientific disciplines in biology over time, ever-smaller structures have come into
focus and more detailed questions have been asked. With the availability of high-throughput sequencing techniques
in genetics a turning point was reached at the molecular basis of life. The frontiers of research extended to hypothesis-
free data acquisition of biological entities, with genomics becoming the first in a growing series of “-omics” disci-
plines. Although functional genomics and proteomics are far from being completed, “omics” -type approaches
addressing the phenotypical cellular, tissue and physiological levels constitute themselves as new scientific disci-
plines, filling up an otherwise sparse data space. Computational systems biology provides methodologies to com-
bine, model, and simulate entities on diverse (horizontal) levels of biological organization, such as gene regulatory
and protein networks, and between these levels by using multiscale (vertical) approaches.

bioinformatics tools to collect, store, retrieve, visualize, and analyze complex biological data
has repeatedly proven useful in biological decision support and discovery. Deciphering the
basic building blocks of life is a necessary step in biological research, but provides only lim-
ited knowledge in terms of understanding and predictability. In the early stages the human
genome project stirred the public expectation for a rapid increase in the deciphering of dis-
ease mechanisms, more effective drug development and cure. However, it is well recognized
that the battery of mechanisms involved in the proliferation of complex diseases like cancer,
chronic diseases, or the development of dementias cannot be understood solely on the basis
of knowing all its molecular components.
As a consequence, a lack of system level understanding of cellular dynamics has prevented
a substantial increase in the number of new drugs available for treatment, drug efficacy, or
eradication of any specific diseases. In contrast, pharmaceutical companies are currently lack-
ing criteria to select the most valuable targets, R&D expenses skyrocket, and new drugs rarely
hit the market and often fail in clinical trials, while physicians face an increasing wealth of
information that needs to be interpreted intelligently and holistically.
Analysis of this dilemma reveals primary difficulties due to the enormous biomolecular
complexity, structural and functional unknowns in a large portion of gene products and a
lack of understanding of how the concert of molecular activities transfers into physiological
alterations and disease. It has been long recognized that the understanding of cells as open
systems, interacting with the environment, performing tasks and sustain homeostasis, or bet-
ter homeodynamics (Yates 1992), requires the development of foundations for a general sys-
tems theory that started with the seminal work of Bertalanffy (Von Bertalanffy 1969).
4 1. Introducing Computational Systems Biology

It appears that with the ever increasing quality and quantity of molecular data, mathematical
models of biological processes are even more in demand. For instance, an envisioned blue-
print of complex diseases will not solely consist of descriptive flowcharts as widely found in
scientific literature or in genomic databases. They should rather be based on predictive, rigor-
ously quantitative data-based mathematical models of metabolic pathways, signal transduc-
tion cascades, cell-cell communication, etc. The general focus of biomedical research on
complex diseases needs to change from a primarily steady-state analysis at the molecular
level to a systems biology level capturing the characteristic dynamic behavior. Such biosimu-
lation concepts will continue to transform current diagnostic and therapeutic approaches to
medicine.

2 OVERVIEW OF THE CONTENT

This completely revised, second edition of this book presents examples selected from an
increasingly diverse field of activities, covering basic key methods, development of tools, and
recent applications in many complex areas of computational systems biology. In the follow-
ing, we will broadly review the content of the chapters as they appear in this book, along with
specific introductions and outlooks.
The first section of this book introduces essential foundations of systems biology, princi-
ples of network reconstruction based on high-throughput data with the help of engineering
principles such as control theory. Robert B. Russell, Gordana Apic, Olga Kalinina, Leonardo
Trabuco, Matthew J. Betts, and Qianhao Lu provide an introduction (Chapter 2) on “Structural
Systems Biology: modeling interactions and networks for systems studies.” Molecular mechanisms
provide the most detailed level for a mechanistic understanding of biological complexity. The
current challenges of a structural systems biology are to integrate, utilize, and extend such
knowledge in conjunction with high-throughput studies. Understanding the mechanistic
consequences of multiple alterations in DNA variants, protein structures, and folding are key
tasks of structural bioinformatics.
Principles of protein interactions in pathways and networks are introduced by Hans V.
Westerhoff, Fei He, Ettore Murabito, Frédéric Crémazy, and Matteo Barberis in Chapter 3.
Their contribution is entitled “Understanding principles of the dynamic biochemical networks of life
through systems biology” and discusses a number of basic, more recent and upcoming discover-
ies of network principles. The contributors review analytical procedures from flux balance in
metabolic networks to measures of robustness.
In Chapter 4, Ursula Klingmüller, Marcel Schilling, Sonja Depner, and Lorenza A.
D‘Alessandro review the “Biological foundations of signal transduction and aberrations in disease.”
Signaling pathways process the external signals through complex cellular networks that reg-
ulate biological functions in a context-dependent manner. The authors identify the underly-
ing biological mechanisms influential for signal transduction and introduce the mathematical
tools essential to model signaling pathways and their disease aberrations in a quantitative
fashion.
Further acceleration of progress in pathway reconstruction and analysis is contingent on
the solution of many complexities and new requirements, revolving around the question of
how high-throughput experimental techniques can help to accelerate reconstruction and
 2 Overview of the content 5
simulation of signaling pathways. This is the theme of the review in Chapter 5 by Christina
Kiel and Luis Serrano on the “Complexities underlying a quantitative systems analysis of signaling
networks.” Chapter 6 by Seiya Imoto, Hiroshi Matsuno, Satoru Miyano presents “Gene net-
works: estimation, modeling and simulation.” The authors describe how gene networks can be
reconstructed from microarray gene expression data, which is a contemporary problem. They
also introduce software tools for modeling and simulating gene networks, which is based on
the concept of Petri nets. The authors demonstrate the utility for the modeling and simulation
of the gene network for controlling circadian rhythms.
Section 2 provides an overview of methods, mathematical tools, and examples for model-
ing approaches of dynamic systems. “Standards, platforms, and applications,” as presented by
Herbert Sauro and Stanley Gu in Chapter 8, reviews the trends in developing standards indic-
ative of increasing cooperation within the systems biology community, which emerged in
recent years permitting collaborative projects and exchange of models between different soft-
ware tools. “Databases for systems biology,” as reviewed in Chapter 9 by Juergen Eils, Elena
Herzog, Baerbel Felder, Christian Lawerenz and Roland Eils provide approaches to integrate
information about the responses of biological system to genetic or environmental perturba-
tions. As researchers try to solve biological problems at the level of entire systems, the very
nature of this approach requires the integration of highly divergent data types, and a tight
coupling of three general areas of data generated in systems biology: experimental data, ele-
ments of biological systems, and mathematical models with the derived simulations. Chapter
10 builds on a classical mathematical modeling approach to study patterns of dynamic behav-
iors in biological systems. “Computational models for circadian rhythms - deterministic versus sto-
chastic approaches,” Jean-Christophe Leloup, Didier Gonze and Albert Goldbeter demonstrates
how feedback loops give rise to oscillatory behavior and how several results can be obtained
in models which possess a minimum degree of complexity. Circadian rhythms provide a par-
ticular interesting case-study for showing how computational models can be used to address
a wide range of issues extending from molecular mechanism to physiological disorders.
Reinhard Laubenbacher and Pedro Mendes review “Top-down dynamical modeling of molecu-
lar regulatory networks,” Chapter 11. The modeling framework discussed in this chapter con-
siders mathematical methods addressing time-discrete dynamical systems over a finite state
set applied to decipher gene regulatory networks from experimental data sets. The assump-
tions of final systems states are not only a useful modeling concept, but also serve an explana-
tion of fundamental organization of cellular complexities. Chapter 12, entitled “Multistability
and multicellularity: cell fates as high-dimensional attractors of gene regulatory networks,” by Joseph
X. Zhou and Sui Huang, investigates how the high number of combinatorially possible
expression configurations collapses into a few configurations characteristic of observable cell
fates. These fates are proposed to be high-dimensional attractors in gene activity state space,
and may help to achieve one of the most desirable goal of computational systems biology,
which is the development of whole cell models. In Chapter 13 John Cole, Mike J. Hallock,
Piyush Labhsetwar, Joseph R. Peterson, John E. Stone, and Zaida Luthey-Schulten review
“Whole cell modeling strategies for single cells and microbial colonies,” taking into account spatial
and time-related heterogeneities such as short-term and long-term stochastic fluctuations.
Section 3 of this book is dedicated to emerging systems biology application including mod-
eling of complex systems and phenotypes in development, aging, health, and disease. In
Chapter 14, Jean-Luc Bouchot, William Trimble, Gregory Ditzler, Yemin Lan, Steve Essinger,
6 1. Introducing Computational Systems Biology

and Gail Rosen introduce “Advances in machine learning for processing and comparison of metage-
nomic data.” The study of nucleic acid samples from different parts of the environment, reflect-
ing the microbiome, has strongly developed in the last years and has become one of the
sustained biocomputational endeavors. Identification, classification, and visualization via
sophisticated computational methods are indispensable in this area. Similarly, the decipher-
ing immune system has to deal with a large amount of data generated from high-throughput
techniques reflecting the inherent complexity of the immune system. Helder I. Nakaya, in
Chapter 15, reports on “Applying systems biology to understand the immune response to infection
and vaccination.” This chapter highlights recent advances and shows how systems biology can
be applied to unravel novel key molecular mechanisms of immunity.
Rene Doursat, Julien Delile, and Nadine Peyrieras present “Cell behavior to tissue deforma-
tion: computational modeling and simulation of early animal embryogenesis,” Chapter 16. They pro-
pose a theoretical, yet realistic agent-based model and simulation platform of animal
embryogenesis, to study the dynamics on multiple levels of biological organization. This con-
tribution is an example demonstrating the value of systems biology in integrating the differ-
ent phenomena involved to study complex biological process. In Chapter 17, Andres Kriete
and Mathieu Cloutier present “Developing a systems biology of aging.” The contribution reviews
modeling of proximal mechanisms of aging occurring in pathways, networks, and multicel-
lular systems, as demonstrated for Parkinson’s disease. In addition, the authors reflect on
evolutionary aspect of aging as a robustness tradeoff in complex biological designs.
In Chapter 18, Hang Chang, Gerald V Fontenay, Ju Han, Nandita Nayak, Alexander
Borowsky, Paul Spellman, and Bahram Parvin present image-based phenotyping strategies
to classify cancer phenotypes on the tissue level, entitled “Morphometric analysis of tissue het-
erogeneity in Glioblastoma Multiforme.” Such work allows to associate morphological heteroge-
neities of cancer subtypes with molecular information to improve prognosis. In terms of a
multiscale modeling approach the assessment of phenotypical changes, in cancer as well as
in other diseases, will help to build bridges toward new spatiotemporal modeling approaches.
Stefan M. Kallenberger, Stefan Legewie, and Roland Eils demonstrate “Applications in cancer
research: mathematical models of apoptosis” in Chapter 19. Their contribution is focused on the
mathematical modeling of cell fate decisions and its dysregulation of cell death, contributing
to one of the ramifications of the complexities in cancer biology.

3 OUTLOOK

It is commonly recognized that biological multiplicity is due to progressive evolution that

brought along an increasing complexity of cells and organisms over time (Adami et al. 2000).
This judgement coincides with the notion that greater complexity is “better” in terms of com-
plex adaptive systems and ability for self-organization, hence robustness (Csete and Doyle
2002 Kitano 2004). Analyzing or “reverse” engineering of this complexity and integrating
results of today’s scientific technologies responsible for the ubiquitous data overload are an
essential part of systems biology. The goals are to conceptualize, abstract basic principles, and
model biological structures from molecular to higher level of organization like cells, tissues,
and organs, in order to provide insight and knowledge. The initial transition requires data
 REFERENCES 7

cleansing and data coherency, but turning information into knowledge requires interpret-
ing what the data actually means. Systems biology addresses this need by the development
and analysis of high-resolution quantitative models that recapitulate, but more importantly
predict cellular behavior in time and space and to determine physiology from the underlying
molecular and cellular capacities on a multiscale (Dada and Mendes 2011). Once established,
such models are indicators to the detailed understanding of biological function, the diagnosis
of diseases, the identification and validation of therapeutic targets, and the design of drugs
and drug therapies. Experimental techniques yielding quantitative genomic, proteomic, and
metabolomic data needed for the development of such models are becoming increasingly
common.
Computer representations describing the underlying mechanisms may not always be able
to provide complete accuracy due to limited computational, experimental, and methodical
resources. Increase in data quality and coherence, availability within integrated databases or
approaches that can manage experimental variability, are less considered but may be as essen-
tial for robust growth of biological knowledge. Still, the enormous complexity of biological
systems has given rise to additional cautionary remarks. First, it may well be that our models
and future super-models correctly predict experimental observations, but may still prevent a
deeper understanding due to complexities, non-linearities, or stochastic phenomena. This
notion may initially sound quite disappointing, but is a daily experience of all those who
employ modeling and simulations of large-scale phenomena. Yet, it shows the relevance of
computational approaches in this area, and suggestions to link biological with computational
problem solving has been suggested (Navlakha and Bar-Joseph 2011).
Systems biology should follow strict standards and conventions, and progress in theory
and computational approaches will always demand new models that can provide new
insights if applied to an existing body of information. Many areas, including cancer model-
ing, have demonstrated how models evolve over many cycles of investigation and refinement
(Byrne 2010). Once established, new models can be reimplemented into existing platforms to
be more broadly available. In the long run, the aim is to develop user-friendly, scalable and
open-ended platforms that also handle methods for behavior analysis and model-based dis-
ease diagnosis, and support scientists in their every-day practice of decision-making and bio-
logical inquiry, as well as physicians in clinical decision support.
Systems biology has risen out of consensus in the scientific community, initially driven by
visionary scientific entrepreneurs. Now, as its strength becomes obvious, it is recognized as a
rapidly evolving mainstream endeavor, which requires specific educational curricula and col-
laboration among computational scientists, experimental and theoretical biologists, control
and systems engineers, as well as practitioners in drug development and clinical research.
These collaborative ties will move this field forwards toward a formal, quantitative, and pre-
dictive framework of biology.

References
Adami, C., Ofria, C., and Collier, T. C. (2000). Evolution of biological complexity. Proc Natl Acad Sci USA
97:4463–4468.
Byrne, H. M. (2010). Dissecting cancer through mathematics: From the cell to the animal model. Nat Rev Cancer
10:221–230.
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Menu suggestion
Serve with green bean-mushroom casserole, baked potatoes,
celery sticks and olives, and orange sherbet.

Stuffed green peppers

6 servings
3 large green peppers
2 teaspoons salt
Boiling water
1 pound ground beef
1½ cups cooked rice
2 tablespoons finely chopped celery
2 tablespoons finely chopped onion
¼ cup chili sauce
2 teaspoons salt
¼ teaspoon pepper
1 egg
2 tablespoons shredded Cheddar cheese
Halve peppers lengthwise; remove stems, seeds, and membranes.
Add 2 teaspoons salt to enough boiling water to cover peppers; boil
peppers 5 minutes. Drain.
Combine other ingredients except cheese; mix well. Fill pepper
halves with this mixture and place in ½ inch of hot water in a baking
pan.
Bake uncovered at 350° F. (moderate oven) 45 to 55 minutes.
Sprinkle cheese over peppers and bake 5 minutes longer, or just
until cheese melts.
Menu suggestion
Serve with corn pudding and coleslaw, and have your favorite ice
cream for dessert.
Saucy luncheon meat
6 servings
2 packages (3 ounces each) cream cheese
2 tablespoons milk
1 pound bologna or other luncheon meat, finely diced
¼ cup finely chopped onion
2 tablespoons sliced ripe olives
2 teaspoons prepared mustard
¾ cup canned condensed cream of mushroom soup
Biscuits, cooked rice, or noodles
Blend cream cheese with milk in top of double boiler. Add meat,
onion, olives, mustard, and soup; mix thoroughly. Heat over
simmering water 15 to 20 minutes, stirring occasionally. Serve over
biscuits, rice, or noodles.
Menu suggestion
Serve with kale, carrot and pineapple salad, and chocolate chip
cookies.

Beef stew
6 servings
⅓ cup flour
1½ teaspoons salt
⅛ teaspoon pepper
1½ pounds boneless stew beef, cut in 1-inch cubes
2 tablespoons fat or oil
3 cups water
3 medium-size onions, sliced
4 medium-size potatoes, cut in 1-inch cubes
5 medium-size carrots, quartered
1½ cups frozen peas
¼ cup water
 Combine flour, salt, and pepper; coat meat with seasoned flour.
Save remaining flour. Brown meat in hot fat in a 4-quart saucepan.
Add water and cover tightly. Simmer until meat is tender, about
1½ hours.
Add onions, potatoes, and carrots. Cover and simmer 15 minutes.
Add peas. Cover and simmer until all vegetables are tender.
Blend ¼ cup water with remaining flour. Add to stew, stirring
gently; cook until thickened.
Variation
Irish stew.—Use lean lamb instead of beef. Add 1 turnip, diced,
with potatoes and carrots.
Menu suggestion
Serve with tossed green salad and hot biscuits. Have fruit sherbet
and cookies for dessert.

Poultry
Serve poultry often—it’s versatile, flavorful, and economical. You
can buy chicken and turkey in convenient sizes—chilled or frozen—
any day of the year. And for variety, try duck and goose.
Preparing poultry
Ready-to-cook poultry needs little preparation before cooking.
Inspect for pinfeathers. Wash and drain poultry.
Keep frozen poultry frozen until time to thaw or cook. Frozen
poultry usually is thawed before cooking, but poultry parts or whole
poultry frozen without giblets can be cooked without thawing.
Cooking time will be longer than for unfrozen poultry. Do not thaw
commercially frozen stuffed poultry before cooking.
To thaw poultry in the refrigerator, place frozen poultry on a tray
or shallow pan to catch the thawing drip; if unwrapped, cover lightly.
Remove giblets from cavity when bird is pliable.
If it is not practical to thaw poultry in the refrigerator, immerse
poultry in a watertight wrapper in cold water. Change water often to
hasten thawing. Or you can partially thaw poultry in the refrigerator
and partially in cold water. It takes 1 to 8 hours to thaw poultry in
cold water, or 1 to 3 days in a refrigerator.
Cook poultry promptly after thawing. Stuff poultry just before
roasting.
Cooking guides
Most poultry sold whole can be roasted. Stewing chickens and
mature turkeys, however, are more tender if braised or stewed. They
are good for stews, or to provide cooked meat for casseroles,
sandwiches, and salads.
Broiler or fryer chickens can be roasted, ovenbaked, barbecued, or
cooked on a rotisserie as well as broiled or fried. Fryer-roaster
turkeys weighing 4 or 5 pounds can be roasted whole, or can be cut
into parts and fried or broiled.
Rock Cornish game hens can be cooked like broiler or fryer
chickens. Small ducks are suitable for broiling or frying; larger ones,
for roasting or rotisserie cooking. Geese roast very well.
Roast poultry uncovered for best color and to reduce splitting and
shrinkage. Poultry can be roasted with or without stuffing; unstuffed
birds take slightly less time to cook. Cook poultry until tender and
juicy; do not overcook.
Roasting
Prepare the poultry as directed above. Stuff the body and neck
cavities lightly; allow about ½ cup of stuffing per pound of ready-to-
cook poultry. See stuffing recipe (p. 28). Or if desired, leave poultry
unstuffed.
Fold loose neck skin toward back; fasten with a skewer. Turn
wingtips back of heavy wingbone to rest against neck skin. Tuck
ends of legs under band of skin at tail or fasten legs together close
to body.
To roast poultry, place breast side up on a rack in a shallow pan.
Do not cover pan and do not add water.
See roasting guide (p. 28) for approximate times for roasting
poultry.
A meat thermometer is the best guide to doneness of turkeys.
Insert the thermometer into the center of the inner thigh muscle.
Make sure it does not touch the bone.
Salt the giblets and neck, seal them in aluminum foil, and roast
along with the poultry. Or simmer them in salted water until tender.
You can baste poultry with pan drippings or a little fat if you like.
If poultry browns early in the roasting period, cover the breast and
drumsticks lightly with aluminum foil or with a thin cloth moistened
with fat. After poultry is partly roasted, cut band of skin that holds
legs together.
Use any one or more of the following ways to tell if poultry is
done:
• A meat thermometer inserted in the center of the inner thigh
muscle of a turkey reaches 180° to 185° F. If turkey is stuffed, also
check stuffing temperature by inserting a thermometer into the body
cavity for 5 minutes. Temperature should reach 165° F.
• Drumstick feels soft when you press meaty part with protected
fingers.
• Drumstick moves up and down easily and leg joint gives readily.
Caution: Do not partly roast poultry on one day and complete
roasting the following day.

ROASTING GUIDE
 Approximate Internal
Ready-to-
roasting time at temperature of
Kind of poultry cook
325° F. for stuffed poultry when
weight[10]
poultry[11] done
Pounds Hours °F.
Chickens 1½ to 2½ 1 to 2
(Broilers, fryers, or
2½ to 4½ 2 to 3½
roasters)
Ducks 4 to 6 2 to 3
Geese 6 to 8 3 to 3½
8 to 12 3½ to 4½
Turkeys 6 to 8 3 to 3½
8 to 12 3½ to 4½ 180 to 185 in
12 to 16 4½ to 5½ center of inner
16 to 20 5½ to 6½ thigh muscle.
20 to 24 6½ to 7

FOOTNOTES:
[10] Weight of giblets and neck included.
[11] Unstuffed poultry may take slightly less time than stuffed
poultry. Cooking time is based on chilled poultry or poultry that
has just been thawed—temperature not above 40° F. Frozen
unstuffed poultry will take longer. Do not use this roasting guide
for frozen commercially stuffed poultry; follow package directions.

Stuffing
About 1 quart
3 tablespoons butter, margarine, or poultry fat
¾ cup chopped celery
3 tablespoons chopped parsley
2 tablespoons chopped onion
1 quart soft breadcrumbs
½ teaspoon savory seasoning
½ teaspoon salt
Pepper, as desired
Melt fat in heavy pan; add celery, parsley, and onion, and cook a
few minutes.
Combine all ingredients. Mix lightly but well.
Use to stuff poultry, or bake in a separate pan during the last hour
of cooking.
Note: Allow about ½ cup stuffing per pound of ready-to-cook
poultry. This stuffing may be used for baked fish, if desired.
Variation
Nut stuffing.—Omit parsley and savory seasoning and add ½ cup
of chopped nutmeats—roasted almonds, pecans, filberts, or cooked
chestnuts.

Braised boneless turkey roast

Place boneless turkey roast on a rack in a pan; insert a meat
thermometer in the center of the roast; cover pan tightly. Braise in
an oven at 400° F. (hot) until thermometer registers about 170° F.
Or, follow cooking directions on package.
Note: A 3-pound boneless turkey roast requires about 1½ hours
cooking time. If desired, uncover roast last 20 minutes to brown.

Broiled chicken
Plump young chicken, about 1½ to 2¼ pounds ready to cook
Melted fat or oil
Salt and pepper, as desired
 Prepare chicken for cooking according to directions on page 26.
Split chicken down the back and, if desired, cut into halves
through the breastbone. Break joints and cut off wingtips.
Brush chicken on both sides with melted fat and sprinkle with salt
and pepper.
Preheat the broiler and grease broiler rack lightly. Place chicken on
the rack, skin side down. Place broiler pan at the distance from heat
recommended by the range manufacturer.
Broil chicken 20 to 30 minutes on one side or until browned; turn,
brush with fat or oil, and broil until done, 15 to 25 minutes longer.
Menu suggestion
Serve with broccoli, creamed potatoes, and lemon chiffon pie.

Stewed chicken
Use a plump stewing chicken, 3 to 4 pounds ready to cook. Or,
you can stew a broiler-fryer chicken, although the flavor will be
somewhat milder.
Prepare chicken for cooking according to the directions on page
26. Leave whole or cut in serving-size pieces.
Place the chicken in a deep pan. Add enough water to half cover a
whole chicken or to cover pieces. Season as desired.
Cover pan and cook over low heat until the chicken is tender—2 to
3 hours for a stewing chicken, 45 minutes to 1 hour for a broiler-
fryer.
Cook giblets with the chicken or separately.
Serve stewed chicken in gravy made by thickening the broth, or
use in any recipe that calls for cooked chicken.

Fried chicken
Plump young chicken, 1½ to 3 pounds ready to cook
Salt, pepper, flour
Fat or oil
Prepare chicken for cooking according to the directions on page
26. Cut in serving pieces.
Season chicken with salt and pepper and roll in flour.
In a heavy frypan, heat ¼ to ¾ cup fat or oil—just enough to
cover bottom of pan. Use moderate heat.
Brown chicken pieces on one side; turn and brown on other side.
Continue to cook slowly, uncovered, until tender. Or, if more
convenient, cook in oven at 350° F. (moderate) until tender. Cooking
time will be from 30 to 45 minutes.
Variation
Oven-fried chicken.—Prepare the chicken according to directions
on page 26. Cut in serving pieces. Preheat oven to 400° F. (hot).
Shake or roll chicken pieces in seasoned flour and place in a baking
pan containing hot fat (⅛ inch deep or less). Turn pieces to coat
both sides with fat. Cook chicken skin side down for 30 minutes;
turn; and cook 20 to 30 minutes longer, or until tender.
Menu suggestion
Serve with mashed potatoes, carrots, and green salad. For dessert
have cherry pie.

Chicken a la king
6 servings
1 cup frozen green peas
2 tablespoons finely chopped onion
¼ cup chopped green pepper
⅓ cup boiling water
⅔ cup flour
1 cup cold milk
2 cups chicken broth
2 teaspoons salt
Pepper, as desired
½ teaspoon poultry seasoning
2 cups diced cooked chicken or turkey
1 can (4 ounces) mushroom stems and pieces, drained and chopped
1 tablespoon chopped pimiento
Cooked rice, toast, or biscuits
Cook peas, onion, and green pepper in boiling water in a covered
pan 5 minutes. Drain; save the liquid.
Blend flour with milk. Combine vegetable cooking liquid, broth,
and seasonings; slowly stir in flour mixture. Bring to a boil, stirring
constantly; cook 1 minute.
Add chicken, cooked vegetables, mushrooms, and pimiento. Heat
thoroughly and serve on rice, toast, or biscuits.
Note: Two chicken bouillon cubes and 2 cups of hot water may be
used to make broth. Decrease salt to 1 teaspoon.
Menu suggestion
Serve with green beans, molded pineapple and carrot salad, and
apple crisp.

Turkey-noodle bake
6 servings
4-ounce package noodles (about 2 cups uncooked)
¼ cup flour
2 cups mushroom liquid and water
2 chicken bouillon cubes
¼ teaspoon salt
Pepper, as desired
½ teaspoon poultry seasoning
1 tablespoon chopped pimiento
4-ounce can mushroom stems and pieces, drained, chopped
2 cups cooked turkey, cubed
¾ cup shredded sharp process cheese
⅓ cup fine dry breadcrumbs
1 tablespoon butter or margarine
Cook noodles as directed on package; drain.
In a saucepan, blend flour with a little of the liquid to make a
paste. Gradually stir in remaining liquid. Add bouillon cubes and
seasonings.
Bring to a boil, stirring constantly. Reduce heat to simmer; cook 1
minute longer, stirring as needed.
Add pimiento and mushrooms to sauce.
In a 2-quart casserole place half the noodles and half the turkey in
layers. Cover with half the sauce. Repeat layers.
Top with cheese; sprinkle with breadcrumbs; dot with fat.
Bake, uncovered, at 350° F. (moderate oven) 30 to 40 minutes or
until bubbly and browned.
Variation
Chicken-noodle bake.—Use chicken instead of turkey, and chicken
broth instead of water and bouillon cubes.
Menu suggestion
Serve with buttered beets, coleslaw, and have ice cream for
dessert.

Chicken pie
6 servings, 9- or 10-inch pie
Filling
3 tablespoons chicken fat, butter, or margarine
¼ cup flour
1¼ cups chicken broth
1 cup milk
1½ teaspoons salt
⅛ teaspoon pepper
¼ teaspoon poultry seasoning, if desired
2 cups cooked chicken, diced
1⅔ cups cooked peas and carrots
Pastry for top crust
1 cup flour
¾ teaspoon baking powder
½ teaspoon salt
⅓ cup shortening
2½ to 3 tablespoons water
Melt fat for the filling in a saucepan; blend in flour. Add broth,
milk, and seasonings. Cook, stirring constantly, until thickened.
Add chicken and vegetables; heat thoroughly.
For the pastry, mix flour, with baking powder and salt.
Mix in fat until mixture is crumbly. Add a little water at a time,
blending lightly.
Dough should be just moist enough to cling together when
pressed into a ball.
Roll dough on a lightly floured surface; shape to fit top of 9- or
10-inch piepan. Make a few small slits near center.
Pour filling into piepan; top with pastry. Turn under pastry edges
and press firmly to pan.
Bake at 400° F. (hot oven) 30 minutes, or until browned.
Variation
 Turkey pie.—Use turkey broth and cooked turkey in place of
chicken broth and cooked chicken.
Menu suggestion
Serve with sliced tomatoes and celery strips and have spicy fruit
for dessert.

Braised chicken with vegetables

6 servings
½ cup flour
1 teaspoon salt
¼ teaspoon pepper
3-pound ready-to-cook broiler-fryer chicken, cut up
3 tablespoons fat or oil
¾ cup hot water
½ teaspoon salt
1½ cups sliced carrots
3 cups sliced celery
¾ cup finely chopped onion
¾ cup chopped green pepper
Combine flour, 1 teaspoon salt, and pepper; coat chicken pieces
with mixture. Brown chicken in hot fat in large frypan. Drain excess
fat from pan. Add water and ½ teaspoon salt. Cover tightly and
simmer 45 minutes to 1 hour, or until chicken is almost tender.
Add vegetables and cook 20 to 30 minutes longer, or until
vegetables are tender.
Menu suggestion
Serve with rice, lettuce and tomato salad, and fruit for dessert.

Homemade noodles with chicken

6 servings
1 cup flour
1 egg or ¼ cup egg yolks (3 or 4 yolks), slightly beaten
1 tablespoon half-and-half or table cream
1½ teaspoons salt
¾ teaspoon poultry seasoning
Pepper, as desired
5 cups chicken broth
3 cups cubed cooked chicken (p. 29)
Paprika
Parsley
Combine first three ingredients thoroughly and form into a ball. Do
not knead. Divide into two parts. Roll each part on lightly floured
surface until paper thin. Allow dough to dry 5 to 10 minutes.
With a thin sharp knife, cut dough into strips of desired width and
length.
Add seasonings to broth; bring to a boil. Add noodles and boil 9 to
12 minutes, or until tender. Add chicken and continue cooking only
until chicken is hot. Sprinkle with paprika and garnish with parsley.
Note: One chicken bouillon cube and 1 cup of water may be used
for each cup of broth; decrease salt to taste.
Timesaver
Use 1½ cups uncooked packaged noodles instead of making
noodles.
Menu suggestion
Serve with broccoli, tossed vegetable salad, and brownies.

Fish
Fish may be cooked by any of the basic methods with excellent
results. Fish should not be overcooked; cook only until it flakes easily
when tested with a fork. This will leave the fish moist and tender
and will bring out its flavor.
Pan-fried fish fillets or steaks
6 servings
2 pounds fish fillets or steaks, fresh or frozen
¼ cup milk
1 egg, beaten
1 teaspoon salt
Pepper, as desired
1½ cups fine dry bread, cereal, or cracker crumbs
Fat or oil
Thaw frozen fish. Cut fish into 6 portions.
Combine milk, egg, salt, and pepper. Dip fish in milk mixture and
roll in crumbs.
Place fish in a single layer in hot fat in a 10-inch frypan. Fry over
moderate heat 4 to 5 minutes, or until brown. Turn carefully. Fry 4 to
5 minutes longer, or until fish are brown and flake easily when tested
with a fork. Drain on absorbent paper.
Variation
Deep-fat fried fish fillets or steaks.—Prepare fish as for pan-fried
fish. Fill fry kettle one-third full of fat; heat to 350° F.
Place fish in a single layer in a fry basket. Fry 3 to 5 minutes, or
until fish are brown and flake easily when tested with a fork. Drain
on absorbent paper.
Menu suggestion
Serve with tartar sauce, baked potatoes, snap beans, tossed green
salad, and upside-down cake.

TIMETABLE FOR COOKING FISH

 Approximate Approximate
Cooking method Cooking
ready-to-cook cooking time in
and market form temperature
weight or thickness minutes
BAKING
3 pounds 350° F. 45 to 60
Dressed
Pan-dressed 3 pounds 350° F. 25 to 30
Fillets or steaks 2 pounds 350° F. 20 to 25
Portions 2 pounds 400° F. 15 to 20
Sticks 2¼ pounds 400° F. 15 to 20

BROILING

Pan-dressed
3 pounds 10 to 16[12]
Fillets or steaks ½ to 1 inch 10 to 15
Portions ⅜ to ½ inch 10 to 15
Sticks ⅜ to ½ inch 10 to 15

CHARCOAL
BROILING

Pan-dressed
3 pounds Moderate 10 to 16[12]
Fillets or steaks ½ to 1 inch Moderate 10 to 16[12]
Portions ⅜ to ½ inch Moderate 8 to 10[12]
Sticks ⅜ to ½ inch Moderate 8 to 10[12]

DEEP-FAT
FRYING
3 pounds 350° F. 3 to 5
Pan-dressed
Fillets or steaks ½ to 1 inch 350° F. 3 to 5
Portions ⅜ to ½ inch 350° F. 3 to 5
Sticks ⅜ to ½ inch 350° F. 3 to 5
OVEN-FRYING
3 pounds 500° F. 15 to 20
Pan-dressed
Fillets or steaks ½ to 1 inch 500° F. 10 to 15

PAN-FRYING

Pan-dressed
3 pounds Moderate 8 to 10[12]
Fillets or steaks ½ to 1 inch Moderate 8 to 10[12]
Portions ⅜ to ½ inch Moderate 8 to 10[12]
Sticks ⅜ to ½ inch Moderate 8 to 10[12]

POACHING
2 pounds Simmer 5 to 10
Fillets or steaks

STEAMING
2 pounds Boil 5 to 10
Fillets or steaks

FOOTNOTES:
[12] Turn once.

Salmon loaf
6 servings
1 can (1 pound) salmon
½ cup milk
3 cups soft breadcrumbs
¼ cup butter or margarine, melted
⅓ cup salmon liquid
3 egg yolks, beaten
2 tablespoons finely chopped green pepper
2 tablespoons finely chopped onion
1 tablespoon lemon juice
⅛ teaspoon pepper
3 egg whites, stiffly beaten
Drain salmon; save the liquid. Flake salmon.
Heat milk. Add breadcrumbs and butter or margarine and let stand
5 minutes. Add salmon liquid and beat until smooth. Add egg yolks,
green pepper, onion, lemon juice, pepper, and salmon; mix well. Fold
in egg whites. Pour into a well-greased 1½-quart loafpan.
Bake at 350° F. (moderate oven) 40 to 50 minutes, or until firm in
center. Remove from oven and let stand 5 minutes. Loosen from
sides of pan with a spatula and invert on a serving platter. Serve
plain or with a sauce.
Menu suggestion
Serve with onion or pea sauce, scalloped potatoes, lettuce salad,
and apple crisp.

Broiled pan-dressed fish

6 servings
3 pounds pan-dressed fish, fresh or frozen
¼ cup melted fat or oil
¼ cup lemon juice
1½ teaspoons salt
¾ teaspoon paprika
Pepper, as desired
Thaw frozen fish. Clean, wash, and dry fish.
 Combine fat and seasonings. Place fish on well-greased broiler
pan. Brush fish inside and out with seasoned fat.
Broil about 4 inches from heat 5 to 8 minutes. Turn fish carefully
and brush on remaining fat. Broil 5 to 8 minutes longer, or until fish
flake easily when tested with a fork.
Menu suggestion
Serve with fried potatoes, spinach, grapefruit salad, and
gingerbread.

Baked fish fillets or steaks

6 servings
2 pounds fish fillets or steaks, fresh or frozen
2 tablespoons melted fat or oil
2 tablespoons lemon juice
1 teaspoon salt
½ teaspoon paprika
Pepper, as desired
Thaw frozen fish. Cut into 6 portions.
Place fish in a single layer, skin side down, in a well-greased
baking dish. Combine remaining ingredients and pour over fish.
Bake at 350° F. (moderate oven) 20 to 25 minutes, or until fish
flake easily when tested with a fork.
Menu suggestion
Serve with french-fried potatoes, cabbage, molded vegetable
salad, and lemon chiffon pie.

Oven-fried fish fillets or steaks

6 servings
2 pounds fish fillets or steaks, fresh or frozen
½ cup milk
1 teaspoon salt
1½ cups cereal crumbs or toasted fine dry bread crumbs
¼ cup melted fat or oil
Thaw frozen fish. Cut into 6 portions.
Combine milk and salt. Dip fish in milk and roll in crumbs. Place
fish in a single layer, skin side down, on a well-greased baking pan.
Pour fat over fish.
Bake at 500° F. (extremely hot oven) 10 to 15 minutes, or until
fish are brown and flake easily when tested with a fork.
Menu suggestion
Serve with broccoli, potatoes with cheese sauce, lettuce salad, and
peach crisp.

Baked stuffed fish

6 servings
1 dressed fish (3 pounds), fresh or frozen
Salt and pepper, as desired
3 cups stuffing (p. 28)
2 tablespoons melted fat or oil
Thaw frozen fish. Clean, wash, and dry fish.
Sprinkle inside with salt and pepper. Place fish on a well-greased
18- by 13-inch bake-and-serve platter. Stuff fish loosely. Brush fish
with fat.
Bake at 350° F. (moderate oven) 45 to 60 minutes, or until the
fish flakes easily when tested with a fork.
Note: Fish may be baked without stuffing.
Menu suggestion
 Serve with broiled tomatoes, peas and celery, coleslaw, and fruit
pie.

Topsy turvy tuna pie

6 servings
1 can (6½ or 7 ounces) tuna
2 tablespoons chopped onion
1 tablespoon tuna oil
1 can (10½ ounces) condensed cream of mushroom soup
2 eggs, beaten
½ cup soft breadcrumbs
6 thin slices lemon or orange
1 package (12 ounces) cornbread or corn muffin mix
Drain tuna; save oil. Flake tuna.
Cook onion in oil until tender. Add soup, eggs, breadcrumbs, and
tuna; mix well. Arrange lemon or orange slices on the bottom of a
well-greased 10-inch piepan. Pour tuna mixture over fruit slices.
Prepare cornbread mix as directed on package. Spread batter over
tuna mixture.
Bake at 400° F. (hot oven) 25 to 30 minutes, or until brown.
Remove from oven and let stand 5 minutes. Loosen from sides of
pan with a spatula and invert on a serving plate.
Menu suggestion
Serve with stewed okra and tomatoes, celery sticks, brownies, and
fruit.

Sardine puff
6 servings
2 cans (3¾ or 4 ounces each) Maine sardines
8 slices white bread
1½ tablespoons butter or margarine
¼ cup chopped green pepper
¾ cup shredded sharp natural Cheddar cheese
3 eggs
½ teaspoon salt
¼ teaspoon dry mustard
Pepper, as desired
2 cups milk
Paprika
Drain sardines and cut into thirds.
Remove crusts from bread, spread with butter or margarine, and
cut bread into ½-inch cubes. Place half the bread cubes in a well-
greased 12- by 8- by 2-inch baking dish. Cover with sardines, green
pepper, and half the cheese. Top with remaining bread cubes and
cheese.
Beat eggs, salt, mustard, and pepper. Add milk and mix well. Pour
over bread and sprinkle with paprika.
Bake at 350° F. (moderate oven) 45 to 50 minutes, or until firm in
the center. Remove from oven and let stand 5 minutes before
serving.
Menu suggestion
Serve with green peas, a relish plate, and orange bavarian cream.

Eggs, cheese, dry beans

Main dishes made with eggs, cheese, or dry beans are economical
choices for family meals.

Cooking eggs
 For best eating quality, eggs should be cooked with low to
moderate heat, for just the right amount of time. If cooking
temperature is too high or the egg is cooked too long, the white
becomes tough and the yolk mealy.

Caution on Use of Cracked or Soiled Eggs

Cracked or soiled eggs may contain bacteria that can produce food
poisoning. For your protection, use cracked or soiled eggs only when
they are thoroughly cooked or when the foods in which they are an
ingredient are thoroughly cooked.
In this publication, a warning note is given with each recipe in
which cracked or soiled eggs should not be used.

Scrambled eggs
Break eggs into a bowl. Add milk as follows: For creamy scrambled
eggs, add 1 tablespoon milk for each ego; for dry scrambled eggs,
add ½ tablespoon milk for each egg. For a product with uniform
yellow color, beat mixture enough to blend yolks and whites
thoroughly. If you prefer scrambled eggs with flecks of yellow and
white, beat only slightly. Season with salt and pepper.
Pour the mixture into a heated frypan in which a little fat has been
melted. Cook slowly, stirring occasionally to let the uncooked portion
flow to the bottom. Cook until the mixture is set, but still moist.
Or, if preferred, use a double boiler. Melt a little fat in the top part,
pour in the egg mixture, place over simmering water in the bottom
of the boiler, and cook as above.
Note: Use only clean, sound-shelled eggs in this recipe.
Variation
 Before cooking the mixture, add herbs, chopped onion, shredded
cheese, or small pieces of cooked bacon or ham.

Eggs cooked in shell

Put eggs in a pan; cover them completely with cold water.
For soft-cooked eggs, heat water slowly to simmering. Cover pan
and remove from heat. Let stand 3 to 5 minutes; allow the longer
time for a larger number of eggs or for a firmer consistency.
Note: Use only clean, sound-shelled eggs in this recipe.
For hard-cooked eggs, bring water to simmering and simmer 20 to
25 minutes. Do not let the water boil. Serve the eggs hot or plunge
them at once into cold running water and leave until cold.
Note: The green discoloration that sometimes appears between
the white and the yolk of a hard-cooked egg results from a chemical
reaction, which is harmless. To help prevent this discoloration, cook
eggs at low temperature, avoid overcooking, and cool promptly.

Fried eggs
Heat a small amount of fat in a frypan. Bacon or ham drippings
may be used for flavor. Break eggs, one at a time, into a saucer, and
slip them into the fat. Sprinkle with salt and pepper. Cook over low
heat, basting with the fat, until whites are firm.
Or, if you prefer eggs with less fat, use this “fry-poach” method.
Melt a little fat in a frypan over low heat—just enough to grease the
bottom. Add eggs one at a time, pour in 2 or 3 tablespoons of water,
cover pan tightly, and steam until eggs are done. Season before
serving.
Note: Use only clean, sound-shelled eggs in this recipe.

French toast
6 servings
4 eggs, beaten
⅔ cup milk
¼ teaspoon salt
12 slices white bread
2 tablespoons fat or oil
Combine eggs, milk, and salt. Dip each side of bread in egg
mixture.
Brown on both sides in fat on a hot griddle—3 to 4 minutes on
each side. Serve immediately.
Note: Use only clean, sound-shelled eggs in this recipe.
Variation
Add ½ teaspoon cinnamon or nutmeg to egg mixture before
dipping bread.

Plain or french omelet

6 servings
6 eggs
¾ teaspoon salt
Pepper, as desired
6 tablespoons milk
3 tablespoons butter or margarine
Beat eggs until yolks and whites are well mixed.
Add salt, pepper, and milk.
Melt the fat in a large frypan and pour in the egg mixture.
Cook over moderate heat. As the omelet cooks, lift edges toward
center and tip pan so that the uncooked mixture flows under the
cooked portion. Continue cooking until bottom is light brown.
Fold one half of the omelet over the other half and serve at once.
 Note: Use only clean, sound-shelled eggs in this recipe.
Variations
Spread tart jelly or browned mushrooms on half the omelet just
before folding.
Sprinkle top of the omelet with shredded cheese, your favorite
herbs, or bits of crisp bacon or ham.

Poached eggs
Break eggs into a saucer or custard cup, one at a time, then slip
them into gently boiling, salted water—enough water to cover the
eggs in a shallow pan.
Reheat water to simmering, take pan from heat, cover. Let stand 5
minutes, or until eggs are of desired firmness. Remove eggs from
water and sprinkle with salt and pepper.
Note: Use only clean, sound-shelled eggs in this recipe.

Poached eggs supreme

6 servings
1 can (10½ ounces) condensed Cheddar cheese soup
2 tablespoons chopped green pepper
¼ cup process sharp Cheddar cheese spread
6 slices toast
6 eggs
Combine soup and green pepper; heat. Spread cheese on toast.
Poach eggs until firm (p. 38). Place eggs on toast and cover with hot
soup mixture. Serve immediately.
Note: Use only clean, sound-shelled eggs in this recipe.
Menu suggestion
 Serve with green beans, fruit salad, and oatmeal cookies.

Deviled eggs
6 servings
6 eggs
¼ cup mayonnaise
1 teaspoon prepared mustard
½ teaspoon vinegar
¼ teaspoon salt
White pepper, as desired
Paprika
Hard-cook eggs as directed on page 37. Cool eggs under cold
running water 5 to 10 minutes. Peel shells from eggs. Cut eggs in
half lengthwise. Mash yolks with remaining ingredients except
paprika until mixture is smooth. Fill whites with this mixture; sprinkle
with paprika.
Variation
Ham-deviled eggs.—Omit salt. Add 1 can (2¼ ounces) deviled
ham to yolk mixture.

Baked eggs in hash nests

6 servings
1 can (1 pound, 8 ounces) corned beef hash
6 eggs
2 tablespoons fine dry breadcrumbs, if desired
Salt and pepper, as desired
1 tablespoon butter or margarine
Spread hash evenly in a 10½- by 7- by 2-inch baking pan. Form
six depressions by pressing the bottom of a ½-cup measure into the
hash.
 Break an egg into each depression. Sprinkle each egg with
breadcrumbs, if desired. Sprinkle with salt and pepper; dot with fat.
Bake at 325° F. (slow oven) 20 to 25 minutes, or until eggs are as
firm as desired.
Note: Use only clean, sound-shelled eggs in this recipe.
Menu suggestion
Serve with mixed vegetables, lettuce wedges, and brownies.

Cooking cheese
Cheese, like eggs, should be cooked at low temperatures and
never overcooked.
Melt cheese over simmering water, or add it to a hot mixture. Add
cheese to a sauce after the sauce is cooked and heat only long
enough to melt the cheese. Add cheese to an omelet just before
folding.
Bake casseroles containing cheese at low to moderate
temperatures. To keep cheese toppings from toughening or
hardening, cover the cheese with crumbs or add cheese just a few
minutes before the casserole comes out of the oven.
Cheese blends more readily with other ingredients and melts more
quickly if you shred or dice it first.

Spanish rice with cheese

6 servings
3 slices bacon
1 small onion, finely chopped
¼ cup chopped green pepper
¼ cup chopped celery
1 cup water
½ teaspoon salt
¾ cup packaged precooked rice
2 cups cooked or canned tomatoes
1 teaspoon sugar
¼ teaspoon worcestershire sauce
1 cup shredded Cheddar cheese
Fry bacon in a heavy 2-quart saucepan. Drain bacon on paper. In
1 tablespoon bacon drippings, lightly brown onion, green pepper,
and celery.
Add water and salt; bring to a boil. Stir in rice, tomatoes, sugar,
and worcestershire sauce. Simmer until rice is just tender, stirring
occasionally.
Crumble bacon and stir into rice mixture. Sprinkle cheese over top.
Cover and continue cooking over very low heat until cheese is
melted, about 5 minutes.
Menu suggestion
Serve with kale, fruit salad, and ice cream.

Pizza
2 pizzas, 14 inches in diameter
1 yeast roll recipe (p. 59)
4 cups shredded cheese (Mozzarella, Muenster, Colby, or process
Swiss or Cheddar)
2 cans (8 ounces each) Spanish-style tomato sauce
½ teaspoon oregano
½ cup grated Parmesan cheese
Preheat oven with oven regulator set at broil; leave oven door
closed.
Prepare roll dough as directed in recipe, but do not allow to rise.
Divide dough into two equal portions; form each into a ball. On a
floured surface, roll out each ball of dough into a 14-inch circle.
Place on lightly greased pizza pans or baking sheets, turning up
edges of dough slightly to form rim.
Sprinkle each pizza with 2 cups shredded cheese. Combine tomato
sauce and oregano; spread half the mixture over each pizza.
Sprinkle half the Parmesan cheese over each pizza.
Place pizzas in preheated oven and turn oven regulator to 525° F.
(extremely hot). Bake 20 to 25 minutes, or until crust is crisp.
Note: Any of toppings below may be added before Parmesan
cheese. Amounts are for 1 pizza:
1 can (8 ounces) sliced mushrooms, drained
¾ pound ground beef, browned and drained
¼ pound pepperoni, thinly sliced
¾ pound fresh pork sausage, browned and drained
Menu suggestion
Serve with mixed vegetable salad and fruit for dessert.

Macaroni with cheese sauce

6 servings
¼ cup butter or margarine
¼ cup flour
½ teaspoon salt
2 cups milk
½ teaspoon mustard
1½ cups cut-up processed Cheddar cheese
3 cups cooked macaroni
Melt fat and mix in flour and salt. Add milk slowly, stirring
constantly, until sauce starts to boil. Lower heat and cook 3 minutes,
or until thick.
Add mustard and cheese. Stir over low heat until cheese softens.
Mix in cooked macaroni and heat through.