Predicting genetic regulatory response using classification. - Manuel Middendorf; Anshul Kundaje; Chris Wiggins 001; Yoav Freund; Christina S. Leslie (ISMB/ECCB (Supplement of Bioinformatics), 2004)

Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response. - Manuel Middendorf; Anshul Kundaje; Chris Wiggins 001; Yoav Freund; Christina S. Leslie (Regulatory Genomics, 2004)

Spectrogram Analysis of Genomes. - David Sussillo; Anshul Kundaje; Dimitris Anastassiou (EURASIP J. Adv. Signal Process., 2004)

Motif Discovery Through Predictive Modeling of Gene Regulation. - Manuel Middendorf; Anshul Kundaje; Mihir Shah; Yoav Freund; Chris Wiggins 001; Christina S. Leslie (RECOMB, 2005)

Combining Sequence and Time Series Expression Data to Learn Transcriptional Modules. - Anshul Kundaje; Manuel Middendorf; Feng Gao; Chris Wiggins 001; Christina S. Leslie (IEEE ACM Trans. Comput. Biol. Bioinform., 2005)

A classification-based framework for predicting and analyzing gene regulatory response. - Anshul Kundaje; Manuel Middendorf; Mihir Shah; Chris Wiggins 001; Yoav Freund; Christina S. Leslie (BMC Bioinform., 2006)

A Predictive Model of the Oxygen and Heme Regulatory Network in Yeast. - Anshul Kundaje; Xiantong Xin; Changgui Lan; Steve Lianoglou; Mei Zhou; Li Zhang 014; Christina S. Leslie (PLoS Comput. Biol., 2008)

Clustering reveals ubiquitous heterogeneity and asymmetry of genomic signals at functional elements. - Anshul Kundaje; Sofia Kyriazopoulou-Panagiotopoulou; Max W. Libbrecht; Cheryl L. Smith; Debasish Raha; Elliott E. Winters; Steven M. Johnson; Michael P. Snyder; Serafim Batzoglou; Arend Sidow (Adv. Math. Commun., 2013)

Comparative analysis of regulatory information and circuits across distant species Open. - Alan P. Boyle; Carlos L. Araya; Cathleen Brdlik; Philip Cayting; Chao Cheng; Yong Cheng; Kathryn Gardner; LaDeana W. Hillier; Judith Janette; Lixia Jiang; Dionna Kasper; Trupti Kawli; et al. (Nat., 2014)

Comparative analysis of metazoan chromatin organization Open. - Joshua Wing Kei Ho; Youngsook L. Jung; Tao Liu 022; Burak Han Alver; Soohyun Lee; Kohta Ikegami; Kyung-Ah Sohn; Aki Minoda; Michael Y. Tolstorukov; Alex Appert; Stephen C. J. Parker; Tingting Gu; et al. (Nat., 2014)

Integrative analysis of 111 reference human epigenomes Open. - Roadmap Epigenomics Consortium; Anshul Kundaje; Wouter Meuleman; Jason Ernst; Misha Bilenky; Angela Yen; Alireza Heravi Moussavi; Pouya Kheradpour; ZhiZhuo Zhang; Jianrong Wang; Michael J. Ziller; Viren Amin; et al. (Nat., 2015)

Unsupervised Learning from Noisy Networks with Applications to Hi-C Data. - Bo Wang 044; Junjie Zhu; Armin Pourshafeie; Oana Ursu; Serafim Batzoglou; Anshul Kundaje (NIPS, 2016)

Not Just a Black Box: Learning Important Features Through Propagating Activation Differences. - Avanti Shrikumar; Peyton Greenside; Anna Shcherbina; Anshul Kundaje (CoRR, 2016)

Learning Important Features Through Propagating Activation Differences. - Avanti Shrikumar; Peyton Greenside; Anshul Kundaje (ICML, 2017)

Denoising genome-wide histone ChIP-seq with convolutional neural networks. - Pang Wei Koh; Emma Pierson; Anshul Kundaje (Bioinform., 2017)

Vicus: Exploiting local structures to improve network-based analysis of biological data. - Bo Wang 044; Lin Huang; Yuke Zhu; Anshul Kundaje; Serafim Batzoglou; Anna Goldenberg (PLoS Comput. Biol., 2017)

Prediction of protein-ligand interactions from paired protein sequence motifs and ligand substructures. - Peyton Greenside; Maureen Hillenmeyer; Anshul Kundaje (PSB, 2018)

Discovering epistatic feature interactions from neural network models of regulatory DNA sequences. - Peyton Greenside; Tyler Shimko; Polly Fordyce; Anshul Kundaje (Bioinform., 2018)

GenomeDISCO: a concordance score for chromosome conformation capture experiments using random walks on contact map graphs. - Oana Ursu; Nathan Boley; Maryna Taranova; Y. X. Rachel Wang; Galip Gürkan Yardimci; William Stafford Noble; Anshul Kundaje (Bioinform., 2018)

Learning to Abstain via Curve Optimization. - Amr Alexandari; Avanti Shrikumar; Anshul Kundaje (CoRR, 2018)

Computationally Efficient Measures of Internal Neuron Importance. - Avanti Shrikumar; Jocelin Su; Anshul Kundaje (CoRR, 2018)

TF-MoDISco v0.4.4.2-alpha: Technical Note. - Avanti Shrikumar; Katherine Tian; Anna Shcherbina; Ziga Avsec; Abhimanyu Banerjee; Mahfuza Sharmin; Surag Nair; Anshul Kundaje (CoRR, 2018)

Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts. - Surag Nair; Daniel S. Kim; Jacob Perricone; Anshul Kundaje (Bioinform., 2019)

GkmExplain: fast and accurate interpretation of nonlinear gapped k-mer SVMs. - Avanti Shrikumar; Eva Prakash; Anshul Kundaje (Bioinform., 2019)

Calibration with Bias-Corrected Temperature Scaling Improves Domain Adaptation Under Label Shift in Modern Neural Networks. - Avanti Shrikumar; Anshul Kundaje (CoRR, 2019)

Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation. - Amr Alexandari; Anshul Kundaje; Avanti Shrikumar (ICML, 2020)

Fourier-transform-based attribution priors improve the interpretability and stability of deep learning models for genomics. - Alex Tseng; Avanti Shrikumar; Anshul Kundaje (NeurIPS, 2020)

WILDS: A Benchmark of in-the-Wild Distribution Shifts. - Pang Wei Koh; Shiori Sagawa; Henrik Marklund; Sang Michael Xie; Marvin Zhang; Akshay Balsubramani; Weihua Hu; Michihiro Yasunaga; Richard Lanas Phillips; Sara Beery; Jure Leskovec; Anshul Kundaje; et al. (CoRR, 2020)

WILDS: A Benchmark of in-the-Wild Distribution Shifts. - Pang Wei Koh; Shiori Sagawa; Henrik Marklund; Sang Michael Xie; Marvin Zhang; Akshay Balsubramani; Weihua Hu; Michihiro Yasunaga; Richard Lanas Phillips; Irena Gao; Tony Lee; Etienne David; et al. (ICML, 2021)

Towards More Realistic Simulated Datasets for Benchmarking Deep Learning Models in Regulatory Genomics. - Eva Prakash; Avanti Shrikumar; Anshul Kundaje (MLBC, 2021)

Towards a Better Understanding of Reverse-Complement Equivariance for Deep Learning Models in Genomics. - Hannah Zhou; Avanti Shrikumar; Anshul Kundaje (MLBC, 2021)

fastISM: performantin silicosaturation mutagenesis for convolutional neural networks. - Surag Nair; Avanti Shrikumar; Jacob M. Schreiber; Anshul Kundaje (Bioinform., 2022)

Accelerating in silico saturation mutagenesis using compressed sensing. - Jacob M. Schreiber; Surag Nair; Akshay Balsubramani; Anshul Kundaje (Bioinform., 2022)

Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design. - AkshatKumar Nigam; Robert Pollice; Gary Tom; Kjell Jorner; Luca A. Thiede; Anshul Kundaje; Alán Aspuru-Guzik (CoRR, 2022)

Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design. - AkshatKumar Nigam; Robert Pollice; Gary Tom; Kjell Jorner; John Willes; Luca A. Thiede; Anshul Kundaje; Alán Aspuru-Guzik (NeurIPS, 2023)

GENCODE: reference annotation for the human and mouse genomes in 2023. - Adam Frankish; Silvia Carbonell Sala; Mark Diekhans; Irwin Jungreis; Jane E. Loveland; Jonathan M. Mudge; Cristina Sisu; James C. Wright; Carme Arnan; If Barnes; Abhimanyu Banerjee; Ruth Bennett; et al. (Nucleic Acids Res., 2023)

DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNA. - Aman Patel; Arpita Singhal; Austin Wang; Anusri Pampari; Maya Kasowski; Anshul Kundaje (NeurIPS, 2024)

Sequence-Based TCR-Peptide Representations Using Cross-Epitope Contrastive Fine-Tuning of Protein Language Models. - Chiho Im; Ryan Zhao; Scott D. Boyd; Anshul Kundaje (RECOMB, 2025)