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Genes, proteins and other biological entities influence one another via causal molecular networks.
On a test of whether one of two random variables is stochastically larger than the other
Henry B Mann and Donald R Whitney · 1947
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Raised conditional level of significance for the 2 × \times 2-table when testing the equality of two probabilities
RD Boschloo · 1970
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Controlling the false discovery rate: a practical and powerful approach to multiple testing
Yoav Benjamini and Yosef Hochberg · 1995
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A programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity
Martin Jinek, Krzysztof Chylinski, Ines Fonfara, Michael Hauer, Jennifer A Doudna, and Emmanuelle Charpentier · 2012
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Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression
Lei S Qi, Matthew H Larson, Luke A Gilbert, Jennifer A Doudna, Jonathan S Weissman, Adam P Arkin, and Wendell A Lim · 2013
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Perturb-Seq: dissecting molecular circuits with scalable single-cell RNA profiling of pooled genetic screens
Atray Dixit, Oren Parnas, Biyu Li, Jenny Chen, Charles P Fulco, Livnat Jerby-Arnon, Nemanja D Marjanovic, Danielle Dionne, Tyler Burks, Raktima Raychowdhury, et al · 2016
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Reference sequence (refseq) database at ncbi: current status, taxonomic expansion, and functional annotation
Nuala A O’Leary, Mathew W Wright, J Rodney Brister, Stacy Ciufo, Diana Haddad, Rich McVeigh, Bhanu Rajput, Barbara Robbertse, Brian Smith-White, Danso Ako-Adjei, et al · 2016
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Causal structure learning
Christina Heinze-Deml, Marloes H Maathuis, and Nicolai Meinshausen · 2018
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Causal learning via manifold regularization
Steven M Hill, Chris J Oates, Duncan A Blythe, and Sach Mukherjee · 2019
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Pangaea: A modular and extensible collection of tools for mining context dependent gene relationships from the biomedical literature
Liviu Pirvan and Shamith A Samarajiwa · 2020
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Causalbench: A large-scale benchmark for network inference from single-cell perturbation data
Mathieu Chevalley, Yusuf Roohani, Arash Mehrjou, Jure Leskovec, and Patrick Schwab · 2022
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Mapping information-rich genotype-phenotype landscapes with genome-scale perturb-seq
Joseph M Replogle, Reuben A Saunders, Angela N Pogson, Jeffrey A Hussmann, Alexander Lenail, Alina Guna, Lauren Mascibroda, Eric J Wagner, Karen Adelman, Gila Lithwick-Yanai, et al · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Cited alongside, same era.
Causal reasoning and large language models: Opening a new frontier for causality
Emre Kıcıman, Robert Ness, Amit Sharma, and Chenhao Tan · 2023
Cited alongside, same era.
Moca: Measuring human-language model alignment on causal and moral judgment tasks
Allen Nie, Yuhui Zhang, Atharva Shailesh Amdekar, Chris Piech, Tatsunori B Hashimoto, and Tobias Gerstenberg · 2023
Cited alongside, same era.
Crab: Assessing the strength of causal relationships between real-world events
Cladder: A benchmark to assess causal reasoning capabilities of language models
Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng Lyu, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, et al · 2024
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Entrez Direct: E-utilities on the Unix Command Line
Jonathan Kans · 2024
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Simulation-based Benchmarking for Causal Structure Learning in Gene Perturbation Experiments
Luka Kovačević, Izzy Newsham, Sach Mukherjee, and John Whittaker · 2024
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Augmenting large language models with chemistry tools
Andres M. Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D White, and Philippe Schwaller · 2024
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Enhancing generative perturbation models with LLM-informed gene embeddings
Kaspar Märtens, Rory Donovan-Maiye, and Jesper Ferkinghoff-Borg · 2024
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Angelika Romanou, Syrielle Montariol, Debjit Paul, Leo Laugier, Karl Aberer, and Antoine Bosselut · 2023
Cited alongside, same era.
The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest
Damian Szklarczyk, Rebecca Kirsch, Mikaela Koutrouli, Katerina Nastou, Farrokh Mehryary, Radja Hachilif, Annika L Gable, Tao Fang, Nadezhda T Doncheva, Sampo Pyysalo, et al · 2023
Cited alongside, same era.
GenePT: a simple but effective foundation model for genes and cells built from ChatGPT
Yiqun Chen and James Zou · 2024
Cited alongside, same era.
Automating exploratory proteomics research via language models
Ning Ding, Shang Qu, Linhai Xie, Yifei Li, Zaoqu Liu, Kaiyan Zhang, Yibai Xiong, Yuxin Zuo, Zhangren Chen, Ermo Hua, et al · 2024
Cited alongside, same era.
Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, et al · 2024
Cited alongside, same era.
Aaron Jaech, Adam Kalai, Adam Lerer, Adam Richardson, Ahmed El-Kishky, Aiden Low, Alec Helyar, Aleksander Madry, Alex Beutel, Alex Carney, et al · 2024
Cited alongside, same era.
The virtual lab: AI agents design new SARS-CoV-2 nanobodies with experimental validation
Kyle Swanson, Wesley Wu, Nash L Bulaong, John E Pak, and James Zou · 2024
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A benchmark for prediction of transcriptomic responses to chemical perturbations across cell types
Artur Szałata, Andrew Benz, Robrecht Cannoodt, Mauricio Cortes, Jason Fong, Sunil Kuppasani, Richard Lieberman, Tianyu Liu, Javier A Mas-Rosario, Rico Meinl, et al · 2024
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Gemma 2: Improving open language models at a practical size
Gemma Team, Morgane Riviere, Shreya Pathak, Pier Giuseppe Sessa, Cassidy Hardin, Surya Bhupatiraju, Léonard Hussenot, Thomas Mesnard, Bobak Shahriari, Alexandre Ramé, et al · 2024
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PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge
Chih-Hsuan Wei, Alexis Allot, Po-Ting Lai, Robert Leaman, Shubo Tian, Ling Luo, Qiao Jin, Zhizheng Wang, Qingyu Chen, and Zhiyong Lu · 2024
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PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis
Yan Wu, Esther Wershof, Sebastian M Schmon, Marcel Nassar, Błażej Osiński, Ridvan Eksi, Kun Zhang, and Thore Graepel · 2024
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