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1Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas. - PubMed - NCBI
Cell Rep. 2018 Apr 3;23(1):239-254.e6. doi: 10.1016/j.celrep.2018.03.076.
6 years ago by @marcsaric
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1Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5902191/
6 years ago by @marcsaric
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1Yellowbrick: Machine Learning Visualization — yellowbrick 0.8 documentation
http://www.scikit-yb.org/en/latest/
6 years ago by @marcsaric
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1Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas. - PubMed - NCBI
Cell Rep. 2018 Apr 3;23(1):172-180.e3. doi: 10.1016/j.celrep.2018.03.046.
6 years ago by @marcsaric
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1A Story of Big Data, Cancer, and Collaboration | DataEDGE Conference
https://dataedge.ischool.berkeley.edu/2017/schedule/story-big-data-cancer-and-collaboration
6 years ago by @marcsaric
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1Macro-causality and social science | Apparent Horizons
https://apparenthorizons.com/2017/11/12/macro-causality-and-social-science/
6 years ago by @marcsaric
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13Blue1Brown - YouTube - YouTube
3Blue1Brown, by Grant Sanderson, is some combination of math and entertainment, depending on your disposition. The goal is for explanations to be driven by a...
7 years ago by @marcsaric
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6An Introduction to Statistical Learning with Applications in R
http://www-bcf.usc.edu/~gareth/ISL/
7 years ago by @marcsaric
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1A Neural Network Playground
http://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle&regDataset=reg-plane&learningRate=0.03&regularizationRate=0&noise=0&networkShape=4,2&seed=0.14753&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false
7 years ago by @marcsaric
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1Research Blog: Distill: Supporting Clarity in Machine Learning
https://research.googleblog.com/2017/03/distill-supporting-clarity-in-machine.html?utm_campaign=Data%2BElixir&utm_medium=web&utm_source=Data_Elixir_124
8 years ago by @marcsaric
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1Deep Learning in 7 lines of code – Chatbot’s Life
https://chatbotslife.com/deep-learning-in-7-lines-of-code-7879a8ef8cfb
8 years ago by @marcsaric
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1Laurae2/Laurae: Advanced High Performance Data Science Toolbox for R by Laurae
https://github.com/Laurae2/Laurae
8 years ago by @marcsaric
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1Comparative analysis of transcriptomic profile, histology, and IDH mutation for classification of gliomas
P. Tran, L. Tran, J. Nechtman, B. dos Santos, S. Purohit, K. Satter, B. Dun, R. Kolhe, S. Sharma, R. Bollag and 1 other author(s). Scientific Reports, 10 (1): 20651-- (2020)
4 years ago by @marcsaric
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1Machine Learning Identifies Robust Matrisome Markers and Regulatory Mechanisms in Cancer
A. Kääriäinen, V. Pesola, A. Dittmann, J. Kontio, J. Koivunen, T. Pihlajaniemi, and V. Izzi. International Journal of Molecular Sciences, 21 (22): 8837 (November 2020)
4 years ago by @marcsaric
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1A meta-learning approach for genomic survival analysis
Y. Qiu, H. Zheng, A. Devos, H. Selby, and O. Gevaert. Nature Communications, 11 (1): 6350-- (2020)
4 years ago by @marcsaric
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1Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework
M. Ali, M. Berrendorf, C. Hoyt, L. Vermue, M. Galkin, S. Sharifzadeh, A. Fischer, V. Tresp, and J. Lehmann. (2020)cite arxiv:2006.13365.
4 years ago by @marcsaric
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1oposSOM: R-package for high-dimensional portraying of genome-wide expression landscapes on bioconductor
H. Löffler-Wirth, M. Kalcher, and H. Binder. Bioinformatics, 31 (19): 3225-3227 (October 2015)
5 years ago by @marcsaric
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2Expression cartography of human tissues using self organizing maps
H. Wirth, M. Löffler, M. von Bergen, and H. Binder. BMC Bioinformatics, (July 2011)
5 years ago by @marcsaric
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1Using Supervised Learning Methods for Gene Selection in RNA-Seq Case-Control Studies
S. Wenric, and R. Shemirani. Frontiers in Genetics, (August 2018)
5 years ago by @marcsaric
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1Combined SOM-portrayal of gene expression and DNA methylation landscapes disentangles modes of epigenetic regulation in glioblastoma
L. Hopp, H. Löffler-Wirth, J. Galle, and H. Binder. Epigenomics, 10 (6): 745--764 (June 2018)
6 years ago by @marcsaric
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1Machine learning and feature selection for drug response prediction in precision oncology applications
M. Ali, and T. Aittokallio. Biophysical Reviews, 11 (1): 31--39 (Feb 1, 2019)
6 years ago by @marcsaric
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2Auto-Encoding Total Correlation Explanation
S. Gao, R. Brekelmans, G. Steeg, and A. Galstyan. (2018)cite arxiv:1802.05822.
6 years ago by @marcsaric
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4Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems
A. Géron. O'Reilly Media, Sebastopol, CA, (2017)
7 years ago by @marcsaric
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2An introduction to statistical learning : with applications in R
G. James. Springer, New York, NY, (2013)
7 years ago by @marcsaric
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2Deep Variational Information Bottleneck
A. Alemi, I. Fischer, J. Dillon, and K. Murphy. (2016)cite arxiv:1612.00410Comment: 19 pages, 8 figures, Accepted to ICLR17.
7 years ago by @marcsaric
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6Opening the Black Box of Deep Neural Networks via Information
R. Shwartz-Ziv, and N. Tishby. (2017)cite arxiv:1703.00810Comment: 19 pages, 8 figures.
7 years ago by @marcsaric
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3An exact mapping between the Variational Renormalization Group and Deep Learning
P. Mehta, and D. Schwab. (2014)cite arxiv:1410.3831Comment: 8 pages, 3 figures.
7 years ago by @marcsaric
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6The information bottleneck method
N. Tishby, F. Pereira, and W. Bialek. (2000)cite arxiv:physics/0004057.
7 years ago by @marcsaric
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2Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data.
S. Monti, P. Tamayo, J. Mesirov, and T. Golub. Machine Learning, 52 (1): 91--118 (2003)
8 years ago by @marcsaric
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10Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow.
F. Giannini, V. Laveglia, A. Rossi, D. Zanca, and A. Zugarini. (2017)cite arxiv:1703.05298.
8 years ago by @marcsaric
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4Deep Forest: Towards An Alternative to Deep Neural Networks.
Z. Zhou, and J. Feng. (2017)cite arxiv:1702.08835Comment: 7 pages, 5 figures.
8 years ago by @marcsaric
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forest
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1Maximally Informative Hierarchical Representations of High-Dimensional Data
G. Steeg, and A. Galstyan. (2014)cite arxiv:1410.7404Comment: 13 pages, 8 figures. Appearing in Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS) 2015.
8 years ago by @marcsaric
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1Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas. - PubMed - NCBI

1Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation

1Yellowbrick: Machine Learning Visualization — yellowbrick 0.8 documentation

1Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas. - PubMed - NCBI

1A Story of Big Data, Cancer, and Collaboration | DataEDGE Conference

1Macro-causality and social science | Apparent Horizons

13Blue1Brown - YouTube - YouTube

6An Introduction to Statistical Learning with Applications in R

1A Neural Network Playground

1Research Blog: Distill: Supporting Clarity in Machine Learning

1Deep Learning in 7 lines of code – Chatbot’s Life

1Laurae2/Laurae: Advanced High Performance Data Science Toolbox for R by Laurae

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1Comparative analysis of transcriptomic profile, histology, and IDH mutation for classification of gliomas

1Machine Learning Identifies Robust Matrisome Markers and Regulatory Mechanisms in Cancer

1A meta-learning approach for genomic survival analysis

1Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework

1oposSOM: R-package for high-dimensional portraying of genome-wide expression landscapes on bioconductor

2Expression cartography of human tissues using self organizing maps

1Using Supervised Learning Methods for Gene Selection in RNA-Seq Case-Control Studies

1Combined SOM-portrayal of gene expression and DNA methylation landscapes disentangles modes of epigenetic regulation in glioblastoma

1Machine learning and feature selection for drug response prediction in precision oncology applications

2Auto-Encoding Total Correlation Explanation

4Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems

2An introduction to statistical learning : with applications in R

2Deep Variational Information Bottleneck

6Opening the Black Box of Deep Neural Networks via Information

3An exact mapping between the Variational Renormalization Group and Deep Learning

6The information bottleneck method

2Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data.

10Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow.

4Deep Forest: Towards An Alternative to Deep Neural Networks.

1Maximally Informative Hierarchical Representations of High-Dimensional Data

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