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Scott J. Emrich
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- affiliation: University of Notre Dame, USA
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2020 – today
- 2023
- [c38]Ashley Nicole Babjac
, Zhixiu Lu
CodonBERT: Using BERT for Sentiment Analysis to Better Predict Genes with Low Expression. BCB 2023: 29:1-29:6 - [c37]Ashley Babjac, Owen Queen, Shawn-Patrick Barhorst, Kambiz Kalhor, Andrew D. Steen, Scott J. Emrich:
Adapting Protein Language Models for Explainable Fine-Grained Evolutionary Pattern Discovery. BIBM 2023: 2609-2616 - [i3]Cai W. John, Owen Queen, Wellington Muchero, Scott J. Emrich:
Deep Learning for Reference-Free Geolocation for Poplar Trees. CoRR abs/2301.13387 (2023) - 2022
- [c36]Ashley Babjac, Taylor M. Royalty, Andrew D. Steen, Scott J. Emrich
A comparison of dimensionality reduction methods for large biological data. BCB 2022: 15:1-15:7 - 2021
- [c35]Ashley Babjac, Jun Li, Scott J. Emrich
Fine-Grained Synonymous Codon Usage Patterns and their Potential Role in Functional Protein Production. BIBM 2021: 2187-2193 - [c34]Owen Queen, Scott J. Emrich
LASSO-based feature selection for improved microbial and microbiome classification. BIBM 2021: 2301-2308 - 2020
- [j21]Khalique Newaz
Network analysis of synonymous codon usage. Bioinform. 36(19): 4876-4884 (2020) - [c33]Ronald J. Nowling, Christopher R. Beal, Scott J. Emrich, Susanta K. Behura, Marc S. Halfon, Molly Duman-Scheel:
PeakMatcher: Matching Peaks Across Genome Assemblies. BCB 2020: 70:1 - [c32]Cai W. John, Wellington Muchero, Scott J. Emrich
Extreme Phenotype Sampling Improves LASSO and Random Forest Marker Selection for Complex Traits. BIBM 2020: 2771-2778
2010 – 2019
- 2019
- [j20]Olivia Choudhury
Highly Accurate and Efficient Data-Driven Methods for Genotype Imputation. IEEE ACM Trans. Comput. Biol. Bioinform. 16(4): 1107-1116 (2019) - [i2]Hongyu Guo, Khalique Newaz, Scott J. Emrich, Tijana Milenkovic, Jun Li:
Weighted graphlets and deep neural networks for protein structure classification. CoRR abs/1910.02594 (2019) - 2018
- [j19]Shenglong Zhu, Scott J. Emrich, Danny Z. Chen:
Inversion detection using PacBio long reads. Int. J. Data Min. Bioinform. 20(3): 230-246 (2018) - [j18]Ronald J. Nowling, Scott J. Emrich
Adjusted likelihood-ratio test for variants with unknown genotypes. J. Bioinform. Comput. Biol. 16(5): 1840020:1-1840020:15 (2018) - [j17]Nicholas L. Hazekamp
Combining Static and Dynamic Storage Management for Data Intensive Scientific Workflows. IEEE Trans. Parallel Distributed Syst. 29(2): 338-350 (2018) - [c31]Ronald J. Nowling, Scott J. Emrich
Detecting Chromosomal Inversions from Dense SNPs by Combining PCA and Association Tests. BCB 2018: 270-276 - [c30]Gabriel Wright, Anabel Rodriguez, Patricia L. Clark, Scott J. Emrich
HarMinMax: Harmonizing Codon Usage to Replicate Local Host Translation. BCB 2018: 528 - [c29]Shenglong Zhu, Scott J. Emrich
Predicting Local Inversions Using Rectangle Clustering and Representative Rectangle Prediction. BIBM 2018: 254-259 - [c28]David C. Molik
Effects from structure of Metabarcode Sequences on Lossy Analysis of Microbiome Data. BIBM 2018: 1832-1837 - [c27]DeAndre A. Tomlinson, David C. Molik
The Effects of Normalization, Transformation, and Rarefaction on Clustering of OTU Abundance. BIBM 2018: 2810-2812 - 2017
- [j16]Julie L. Chaney, Aaron Steele, Rory Carmichael, Anabel Rodriguez, Alicia T. Specht, Kim Ngo, Jun Li
Widespread position-specific conservation of synonymous rare codons within coding sequences. PLoS Comput. Biol. 13(5) (2017) - [c26]Shenglong Zhu, Scott J. Emrich
Inversion detection using PacBio long reads. BIBM 2017: 237-242 - [c25]Ronald J. Nowling, Scott J. Emrich
Stable feature ranking with logistic regression ensembles. BIBM 2017: 585-589 - 2016
- [c24]Olivia Choudhury, Ankush Chakrabarty, Scott J. Emrich
HAPI-Gen: Highly Accurate Phasing and Imputation of Genotype Data. BCB 2016: 78-87 - [c23]Shenglong Zhu, Danny Z. Chen, Scott J. Emrich:
Single molecule sequencing-guided scaffolding and correction of draft assemblies. ICCABS 2016: 1 - [i1]Geoffrey Siwo, Andrew K. Rider, Asako Tan, Richard S. Pinapati
Prediction of fine-tuned promoter activity from DNA sequence. F1000Research 5: 158 (2016) - 2015
- [j15]Andrew S. Warren
RNA-Rocket: an RNA-Seq analysis resource for infectious disease research. Bioinform. 31(9): 1496-1498 (2015) - [j14]Gloria I. Giraldo-Calderón
VectorBase: an updated bioinformatics resource for invertebrate vectors and other organisms related with human diseases. Nucleic Acids Res. 43(Database-Issue): 707-713 (2015) - [j13]Olivia Choudhury, Nicholas L. Hazekamp, Douglas Thain
Accelerating Comparative Genomics Work ows in a Distributed Environment with Optimized Data Partitioning and Workflow Fusion. Scalable Comput. Pract. Exp. 16(1) (2015) - [c22]Erliang Zeng, Wei Zhang, Scott J. Emrich
A computational framework for integrative analysis of large microbial genomics data. BIBM 2015: 1109-1116 - [c21]Olivia Choudhury, Dinesh Rajan, Nicholas L. Hazekamp, Sandra Gesing, Douglas Thain
Balancing Thread-Level and Task-Level Parallelism for Data-Intensive Workloads on Clusters and Clouds. CLUSTER 2015: 390-393 - [c20]Nicholas L. Hazekamp, Joseph Sarro, Olivia Choudhury, Sandra Gesing, Scott J. Emrich
Scaling Up Bioinformatics Workflows with Dynamic Job Expansion: A Case Study Using Galaxy and Makeflow. e-Science 2015: 332-341 - [c19]Lauren A. Assour, Scott J. Emrich
Global maximum-parsimony based ancestral reconstruction with non-universal genes. ICCABS 2015: 1-6 - 2014
- [j12]Irena Lanc, Peter Bui, Douglas Thain
Adapting bioinformatics applications for heterogeneous systems: a case study. Concurr. Comput. Pract. Exp. 26(4): 866-877 (2014) - [j11]Andrew Thrasher
Scaling up genome annotation using MAKER and work queue. Int. J. Bioinform. Res. Appl. 10(4/5): 447-460 (2014) - [j10]Wei Zhang, Erliang Zeng
Mapping genomic features to functional traits through microbial whole genome sequences. Int. J. Bioinform. Res. Appl. 10(4/5): 461-478 (2014) - [j9]Andrew K. Rider, Geoffrey Siwo, Scott J. Emrich
A supervised learning approach to the ensemble clustering of genes. Int. J. Data Min. Bioinform. 9(2): 199-219 (2014) - [c18]Nicholas L. Hazekamp, Olivia Choudhury, Sandra Gesing, Scott J. Emrich
Expanding Tasks of Logical Workflows Into Independent Workflows for Improved Scalability. CCGRID 2014: 548-549 - [c17]Olivia Choudhury, Nicholas L. Hazekamp, Douglas Thain
Accelerating Comparative Genomics Workflows in a Distributed Environment with Optimized Data Partitioning. CCGRID 2014: 711-719 - 2013
- [c16]Dinesh Rajan, Andrew Thrasher
Case Studies in Designing Elastic Applications. CCGRID 2013: 466-473 - [c15]Irena Lanc, Scott J. Emrich:
An unsupervised learning approach to assembly validation. ICCABS 2013: 1-2 - [c14]Wei Zhang, Erliang Zeng
Predicting bacterial functional traits from whole genome sequences using random forest. ICCABS 2013: 1-2 - 2012
- [j8]Karine Megy
VectorBase: improvements to a bioinformatics resource for invertebrate vector genomics. Nucleic Acids Res. 40(Database-Issue): 729-734 (2012) - [j7]Christopher Moretti, Andrew Thrasher
A Framework for Scalable Genome Assembly on Clusters, Clouds, and Grids. IEEE Trans. Parallel Distributed Syst. 23(12): 2189-2197 (2012) - [c13]Scott J. Emrich
Workshop: Opportunities and challenges of non-model ecoinformatics. ICCABS 2012: 1 - [c12]Andrew Thrasher
Shifting the bioinformatics computing paradigm: A case study in parallelizing genome annotation using MAKER and Work Queue. ICCABS 2012: 1-6 - [c11]Wei Zhang, Erliang Zeng
A machine learning framework for trait based genomics. ICCABS 2012: 1-6 - 2011
- [j6]Rory Carmichael, Patrick Braga-Henebry, Douglas Thain
Biocompute 2.0: an improved collaborative workspace for data intensive bio-science. Concurr. Comput. Pract. Exp. 23(17): 2305-2314 (2011) - [c10]Shawn T. O'Neil
Robust haplotype reconstruction of eukaryotic read data with Hapler. ICCABS 2011: 141-146 - 2010
- [j5]Andrew K. Rider, Geoffrey Siwo, Nitesh V. Chawla
A statistical approach to finding overlooked genetic associations. BMC Bioinform. 11: 526 (2010) - [j4]Li Yu, Christopher Moretti, Andrew Thrasher
Harnessing parallelism in multicore clusters with the All-Pairs, Wavefront, and Makeflow abstractions. Clust. Comput. 13(3): 243-256 (2010) - [c9]Wei Zhang, Scott J. Emrich
A two-stage machine learning approach for pathway analysis. BIBM 2010: 274-279 - [c8]Andrew K. Rider, Geoffrey Siwo, Scott J. Emrich
A supervised learning approach to the unsupervised clustering of genes. BIBM 2010: 322-328 - [c7]Rory Carmichael, Patrick Braga-Henebry, Douglas Thain
Biocompute: towards a collaborative workspace for data intensive bio-science. HPDC 2010: 489-498
2000 – 2009
- 2009
- [c6]Allison Regier, Michael Olson, Scott J. Emrich
Alignment and Analysis of Closely Related Genomes. BICoB 2009: 343-352 - [c5]Li Yi, Christopher Moretti, Scott J. Emrich
Harnessing parallelism in multicore clusters with the all-pairs and wavefront abstractions. HPDC 2009: 1-10 - [c4]Christopher Moretti, Michael Olson, Scott J. Emrich
Highly scalable genome assembly on campus grids. SC-MTAGS 2009 - 2007
- [j3]Anantharaman Kalyanaraman, Scott J. Emrich
Assembling genomes on large-scale parallel computers. J. Parallel Distributed Comput. 67(12): 1240-1255 (2007) - [c3]Scott J. Emrich, Anantharaman Kalyanaraman, Srinivas Aluru:
Massively parallel expressed sequence tag clustering. PDCS 2007: 254-261 - 2006
- [c2]Anantharaman Kalyanaraman, Scott J. Emrich
Assembling genomes on large-scale parallel computers. IPDPS 2006 - 2004
- [j2]Scott J. Emrich
A strategy for assembling the maize (Zea mays L.) genome. Bioinform. 20(2): 140-147 (2004) - [c1]Daniel A. Ashlock, Scott J. Emrich, Kenneth Mark Bryden, Steven M. Corns, Tsui-Jung Wen, Patrick S. Schnable
A comparison of evolved finite state classifiers and interpolated Markov models for improving PCR primer design. CIBCB 2004: 190-197 - 2003
- [j1]Scott J. Emrich
PROBEmer: a web-based software tool for selecting optimal DNA oligos. Nucleic Acids Res. 31(13): 3746-3750 (2003)
Coauthor Index
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