Anshul Kundaje
- WILDS: A Benchmark of in-the-Wild Distribution Shifts
2020/12/14 by Pang Wei Koh, Shiori Sagawa, Koh, Pang Wei +43 · 188 citations
Computer Science · Medicine · #AI in cancer detection #COVID-19 diagnosis using AI #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification
- Not Just a Black Box: Learning Important Features Through Propagating Activation Differences
2016/05/05 by Avanti Shrikumar, Peyton Greenside, Shrikumar, Avanti +5 · 33 citations
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification #Neural and Evolutionary Computing (cs.NE)
- Umap and Bismap: quantifying genome and methylome mappability
2018/07/22 by Mehran Karimzadeh, Carl Ernst, Anshul Kundaje +1 · 1 voice · 6 citations
Biochemistry, Genetics and Molecular Biology · #Epigenetics and DNA Methylation #Genomics and Phylogenetic Studies #RNA modifications and cancer
- Technical Note on Transcription Factor Motif Discovery from Importance Scores (TF-MoDISco) version 0.5.6.5
2018/10/31 by Avanti Shrikumar, Shrikumar, Avanti, Katherine Tian +13 · 7 citations
Biochemistry, Genetics and Molecular Biology · #Bioinformatics and Genomic Networks #FOS: Biological sciences #FOS: Computer and information sciences #Genomics (q-bio.GN) #Genomics and Chromatin Dynamics #Genomics and Phylogenetic Studies #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNA
2024/12/06 by Aman Patel, Patel, Aman, Arpita Singhal +9 · 4 voices · 6 citations
#cs.LG #q-bio.GN
- Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design
2022/09/26 by AkshatKumar Nigam, Robert Pollice, Nigam, AkshatKumar +12 · 6 citations
Computer Science · Engineering · Materials Science · #Computational Drug Discovery Methods #Computational Engineering #FOS: Computer and information sciences #Finance #Machine Learning in Materials Science #Process Optimization and Integration #and Science (cs.CE)
- Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries
2022/12/20 by Ceres Fernandez-Rozadilla, Ceres Fernández–Rozadilla, Maria Timofeeva +254 · 5 citations
Biochemistry, Genetics and Molecular Biology · Medicine · #Colorectal Cancer Screening and Detection #Genetic Associations and Epidemiology #Genetic factors in colorectal cancer
- ChromBPNet: bias factorized, base-resolution deep learning models of chromatin accessibility reveal cis-regulatory sequence syntax, transcription factor footprints and regulatory variants
2024/12/25 by Anusri Pampari, Anna Shcherbina, Evgeny Z. Kvon +10 · 1 voice · 6 citations
Biochemistry, Genetics and Molecular Biology · #Epigenetics and DNA Methylation #Genomic variations and chromosomal abnormalities #Genomics and Chromatin Dynamics
- Predicting Genetic Regulatory Response Using Classification
2004/11/12 by Manuel Middendorf, Anshul Kundaje, Chris Wiggins +2 · 1 citation
Biochemistry, Genetics and Molecular Biology · #q-bio.QM
- Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation
2019/01/21 by Amr M. Alexandari, Alexandari, Amr, Anshul Kundaje +3 · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · #Cancer-related molecular mechanisms research #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- JASPAR 2026: expansion of transcription factor binding profiles and integration of deep learning models
2025/12/02 by Damla Ovek, Ieva Rauluševičiūtė, Dina Ruud Aronsen +31 · 2 voices · 4 citations
Biochemistry, Genetics and Molecular Biology · #Developmental Biology and Gene Regulation #Genomics and Chromatin Dynamics #Machine Learning in Bioinformatics
- Computationally Efficient Measures of Internal Neuron Importance
2018/07/26 by Avanti Shrikumar, Jocelin Su, Shrikumar, Avanti +3 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Cell Image Analysis Techniques #Computer Vision and Pattern Recognition (cs.CV) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Neural and Evolutionary Computing (cs.NE)
- Semi-automated genome annotation using epigenomic data and Segway
2016/10/17 by Eric G. Roberts, Mickaël Mendez, Coby Viner +7 · 1 voice · 1 citation
Biochemistry, Genetics and Molecular Biology · #Gene expression and cancer classification #Genomics and Chromatin Dynamics #Genomics and Phylogenetic Studies
- Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk
2023/12/19 by Mariana C. Stern, Joel Sanchez Mendez, Andre E. Kim +69 · 1 voice · 2 citations
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Medicine · #Genetic Associations and Epidemiology #Meat and Animal Product Quality #Nutritional Studies and Diet
- The importance of transparency and reproducibility in artificial intelligence research
2020/02/28 by Benjamin Haibe-Kains, George Alexandru Adam, Ahmed Hosny +17 · 1 voice
Mathematics · #stat.AP
- MorPhiC Consortium: towards functional characterization of all human genes
2025/02/12 by Mazhar Adli, Laralynne Przybyla, Tony Burdett +127 · 1 voice · 4 citations
Biochemistry, Genetics and Molecular Biology · #Single-cell and spatial transcriptomics #CRISPR and Genetic Engineering #Genomics and Chromatin Dynamics