CoGAPS: an R/C++ package to identify patterns and biological process activity in transcriptomic data. - Elana J. Fertig; Jie Ding; Alexander V. Favorov; Giovanni Parmigiani; Michael F. Ochs (Bioinform., 2010)

Cancer Systems Biology. - Elana J. Fertig; Ludmila V. Danilova; Michael F. Ochs (Handbook of Statistical Bioinformatics, 2011)

Identifying context-specific transcription factor targets from prior knowledge and gene expression data. - Elana J. Fertig; Alexander V. Favorov; Michael F. Ochs (BIBM, 2012)

Matrix factorization for transcriptional regulatory network inference. - Michael F. Ochs; Elana J. Fertig (CIBCB, 2012)

Quantifying the Dynamics of Coupled Networks of Switches and Oscillators. - Matthew R. Francis; Elana J. Fertig (RECOMB, 2012)

Preserving biological heterogeneity with a permuted surrogate variable analysis for genomics batch correction. - Hilary S. Parker; Jeffrey T. Leek; Alexander V. Favorov; Michael Considine; Xiaoxin Xia; Sameer Chavan; Christine H. Chung; Elana J. Fertig (Bioinform., 2014)

The estimation of dimensionality in gene expression data using Nonnegative Matrix Factorization. - Conor J. Kelton; Waishing Lee; Matthew Rusay; Ondrej Maxian; Elana J. Fertig; Michael F. Ochs (BIBM, 2015)

switchBox: an R package for k-Top Scoring Pairs classifier development. - Bahman Afsari; Elana J. Fertig; Donald Geman; Luigi Marchionni (Bioinform., 2015)

AGA: Interactive pipeline for reproducible genomics analyses. - Michael Considine; Hilary S. Parker; Yingying Wei; Xaio Xia; Leslie Cope; Michael F. Ochs; Elana J. Fertig (F1000Research, 2015)

StereoGene: rapid estimation of genome-wide correlation of continuous or interval feature data. - Elena D. Stavrovskaya; Tejasvi Niranjan; Elana J. Fertig; Sarah J. Wheelan; Alexander V. Favorov; Andrey A. Mironov (Bioinform., 2017)

PatternMarkers & GWCoGAPS for novel data-driven biomarkers via whole transcriptome NMF. - Genevieve L. Stein-O'Brien; Jacob L. Carey; Waishing Lee; Michael Considine; Alexander V. Favorov; Emily Flam; Theresa Guo; Sijia Li; Luigi Marchionni; Thomas Sherman; Shawn Sivy; Daria A. Gaykalova; et al. (Bioinform., 2017)

Splice Expression Variation Analysis (SEVA) for inter-tumor heterogeneity of gene isoform usage in cancer. - Bahman Afsari; Theresa Guo; Michael Considine; Liliana Florea; Luciane T. Kagohara; Genevieve L. Stein-O'Brien; Dylan Kelley; Emily Flam; Kristina D. Zambo; Patrick K. Ha; Donald Geman; Michael F. Ochs; et al. (Bioinform., 2018)

CancerInSilico: An R/Bioconductor package for combining mathematical and statistical modeling to simulate time course bulk and single cell gene expression data in cancer. - Thomas Sherman; Luciane T. Kagohara; Raymon Cao; Raymond Cheng; Matthew Satriano; Michael Considine; Gabriel Krigsfeld; Ruchira Ranaweera; Yong Tang; Sandra A. Jablonski; Genevieve L. Stein-O'Brien; Daria A. Gaykalova; et al. (PLoS Comput. Biol., 2019)

projectR: an R/Bioconductor package for transfer learning via PCA, NMF, correlation and clustering. - Gaurav Sharma; Carlo Colantuoni; Loyal A. Goff; Elana J. Fertig; Genevieve L. Stein-O'Brien (Bioinform., 2020)

CoGAPS 3: Bayesian non-negative matrix factorization for single-cell analysis with asynchronous updates and sparse data structures. - Thomas Sherman; Tiger Gao; Elana J. Fertig (BMC Bioinform., 2020)

A field guide to cultivating computational biology. - Anne E. Carpenter; Casey S. Greene; Piero Carnici; Benilton S. Carvalho; Michiel de Hoon; Stacey D. Finley; Kim-Anh Lê Cao; Jerry S. H. Lee; Luigi Marchionni; Suzanne Sindi; Fabian J. Theis; Gregory P. Way; et al. (CoRR, 2021)

Ten Quick Tips for Deep Learning in Biology. - Benjamin D. Lee; Anthony Gitter; Casey S. Greene; Sebastian Raschka; Finlay Maguire; Alexander J. Titus; Michael D. Kessler; Alexandra J. Lee; Marc G. Chevrette; Paul Allen Stewart; Thiago Britto-Borges; Evan M. Cofer; et al. (CoRR, 2021)

Regression Expression Variation Analysis (REVA): a rank-based multi-dimensional measure of correlation. - Bahman Afsari; Alexander V. Favorov; Elana J. Fertig; Leslie Cope (ICMLA, 2022)

Ten quick tips for deep learning in biology. - Benjamin D. Lee; Anthony Gitter; Casey S. Greene; Sebastian Raschka; Finlay Maguire; Alexander J. Titus; Michael D. Kessler; Alexandra J. Lee; Marc G. Chevrette; Paul Allen Stewart; Thiago Britto-Borges; Evan M. Cofer; et al. (PLoS Comput. Biol., 2022)

Transcriptomic forecasting with neural ordinary differential equations. - Rossin Erbe; Genevieve L. Stein-O'Brien; Elana J. Fertig (Patterns, 2023)

Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology. - Theinmozhi Arulraj; Hanwen Wang; Alberto Ippolito; Shuming Zhang; Elana J. Fertig; Aleksander S. Popel (Briefings Bioinform., 2024)

Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology. - Haoyang Mi; Shamilene Sivagnanam; Won Jin Ho; Shuming Zhang; Daniel Bergman; Atul Deshpande; Alexander S. Baras; Elizabeth M. Jaffee; Lisa M. Coussens; Elana J. Fertig; Aleksander S. Popel (Briefings Bioinform., 2024)