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High-content perturbation experiments allow scientists to probe biomolecular systems at unprecedented resolution, but experimental and analysis costs pose significant barriers to widespread adoption.
Exploring the potential of large language models (LLMs) in learning on graphs
Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, and Jiliang Tang · 1931
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Individual comparisons by ranking methods
Frank Wilcoxon · 1945
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Gene Ontology: tool for the unification of biology
M Ashburner, C A Ball, J A Blake, D Botstein, H Butler, J M Cherry, A P Davis, K Dolinski, S S Dwight, J T Eppig, M A Harris, D P Hill, L Issel-Tarver, A Kasarskis, S Lewis, J C Matese, J E Richardson, M Ringwald, G M Rubin, and G Sherlock · 2000
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On the adaptive control of the false discovery rate in multiple testing with independent statistics
Yoav Benjamini and Yosef Hochberg · 2000
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
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Statistical tests for differential expression in cDNA microarray experiments
Xiangqin Cui and Gary Churchill · 2003
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Sayan Mukherjee, Benjamin L. Ebert, Michael A. Gillette, Amanda Paulovich, Scott L. Pomeroy, Todd R. Golub, Eric S. Lander, and Jill P. Mesirov · 2005
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Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists
Da Wei Huang, Brad T. Sherman, and Richard A. Lempicki · 2008
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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
M I Love, W Huber, and S Anders · 2014
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Traversing knowledge graphs in vector space
K. Guu, J. Miller, and P. Liang · 2015
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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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Pooled CRISPR screening with single-cell transcriptome readout
Paul Datlinger, André F Rendeiro, Christian Schmidl, Thomas Krausgruber, Peter Traxler, Johanna Klughammer, Linda C Schuster, Amelie Kuchler, Donat Alpar, and Christoph Bock · 2017
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
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Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio · 2017
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A transcriptional MAPK pathway activity score (MPAS) is a clinically relevant biomarker in multiple cancer types
Marie-Claire Wagle, Daniel Kirouac, Christiaan Klijn, Bonnie Liu, Shilpi Mahajan, Melissa Junttila, John Moffat, Ling Huw, Matthew Wongchenko, Kwame Okrah, Shrividhya Srinivasan, Zineb Mounir, Teiko Sumiyoshi, Peter Haverty, Robert Yauch, Yibing Yan, Omar Kabbarah, Garret Hampton, and Shih-Min Huang · 2018
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scGen predicts single-cell perturbation responses
Mohammad Lotfollahi, F. Alexander Wolf, and Fabian J Theis · 2019
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Exploring genetic interaction manifolds constructed from rich single-cell phenotypes
Thomas M. Norman, Max A. Horlbeck, Joseph M. Replogle, Alex Y. Ge, Albert Xu, Marco Jost, Luke A. Gilbert, and Jonathan S. Weissman · 2019
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glmGamPoi: fitting Gamma-Poisson generalized linear models on single cell count data
Constantin Ahlmann-Eltze and Wolfgang Huber · 2020
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BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang · 2020
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Retrieval-augmented generation for knowledge-intensive NLP tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
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BERTScore: Evaluating text generation with BERT
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi · 2020
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2021
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Dual proteome-scale networks reveal cell-specific remodeling of the human interactome
Edward L. Huttlin, Raphael J. Bruckner, Jose Navarrete-Perea, Joe R. Cannon, Kurt Baltier, Fana Gebreab, Melanie P. Gygi, Alexandra Thornock, Gabriela Zarraga, Stanley Tam, John Szpyt, Brandon M. Gassaway, Alexandra Panov, Hannah Parzen, Sipei Fu, Arvene Golbazi, Eila Maenpaa, Keegan Stricker, Sanjukta Guha Thakurta, Tian Zhang, Ramin Rad, Joshua Pan, David P. Nusinow, Joao A. Paulo, Devin K. Schweppe, Laura Pontano Vaites, J. Wade Harper, and Steven P. Gygi · 2021
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UniProt: the Universal Protein Knowledgebase in 2023
The UniProt Consortium · 2022
Cited alongside, same era.
GSEApy: a comprehensive package for performing gene set enrichment analysis in Python
Zhuoqing Fang, Xinyuan Liu, and Gary Peltz · 2022
Cited alongside, same era.
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, Nika Iremadze, Florian Oberstrass, Doron Lipson, Jessica L. Bonnar, Marco Jost, Thomas M. Norman, and Jonathan S. Weissman · 2022
Cited alongside, same era.
AttentionPert: accurately modeling multiplexed genetic perturbations with multi-scale effects
Ding Bai, Caleb N Ellington, Shentong Mo, Le Song, and Eric P Xing · 2024
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Graph of Thoughts: solving elaborate problems with large language models
Maciej Besta, Nils Blach, Ales Kubicek, Robert Gerstenberger, Lukas Gianinazzi, Joanna Gajda, Tomasz Lehmann, Michał Podstawski, Hubert Niewiadomski, Piotr Nyczyk, and Torsten Hoefler · 2024
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scGPT: toward building a foundation model for single-cell multi-omics using generative AI
Haotian Cui, Chloe Wang, Hassaan Maan, Kuan Pang, Fengning Luo, Nan Duan, and Bo Wang · 2024
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
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From local to global: A graph RAG approach to query-focused summarization
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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, Peer Bork, Lars J Jensen, and Christian von Mering · 2022
Cited alongside, same era.
CORUM: the comprehensive resource of mammalian protein complexes–2022
George Tsitsiridis, Ralph Steinkamp, Madalina Giurgiu, Barbara Brauner, Gisela Fobo, Goar Frishman, Corinna Montrone, and Andreas Ruepp · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou · 2022
Cited alongside, same era.
GraphText: Graph reasoning in text space
Jianan Zhao, Le Zhuo, Yikang Shen, Meng Qu, Kai Liu, Michael Bronstein, Zhaocheng Zhu, and Jian Tang · 2022
Cited alongside, same era.
The Gene Ontology knowledgebase in 2023
Suzi A Aleksander, James Balhoff, Seth Carbon, J Michael Cherry, Harold J Drabkin, Dustin Ebert, Marc Feuermann, Pascale Gaudet, Nomi L Harris, et al · 2023
Cited alongside, same era.
Learning single-cell perturbation responses using neural optimal transport
Charlotte Bunne, Stefan G Stark, Gabriele Gut, Jacobo Sarabia Del Castillo, Mitch Levesque, Kjong-Van Lehmann, Lucas Pelkmans, Andreas Krause, and Gunnar Rätsch · 2023
Cited alongside, same era.
GenePT: A simple but effective foundation model for genes and cells built from ChatGPT
Yiqun Chen and James Zou · 2023
Cited alongside, same era.
LMDeploy: A toolkit for compressing, deploying, and serving LLMs
LMDeploy Contributors · 2023
Cited alongside, same era.
Darren Edge, Ha Trinh, Newman Cheng, Joshua Bradley, Alex Chao, Apurva Mody, Steven Truitt, and Jonathan Larson · 2024
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Season combinatorial intervention predictions with Salt & Peper
Thomas Gaudelet, Alice Del Vecchio, Eli M Carrami, Juliana Cudini, Chantriolnt-Andreas Kapourani, Caroline Uhler, and Lindsay Edwards · 2024
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G-retriever: Retrieval-augmented generation for textual graph understanding and question answering
Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, and Bryan Hooi · 2024
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Thought graph: Generating thought process for biological reasoning
Chi-Yang Hsu, Kyle Cox, Jiawei Xu, Zhen Tan, Tianhua Zhai, Mengzhou Hu, Dexter Pratt, Tianlong Chen, Ziniu Hu, and Ying Ding · 2024
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Large language models on graphs: A comprehensive survey
Bowen Jin, Gang Liu, Chi Han, Meng Jiang, Heng Ji, and Jiawei Han · 2024
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scPRINT: pre-training on 50 million cells allows robust gene network predictions
Jérémie Kalfon, Jules Samaran, Gabriel Peyré, and Laura Cantini · 2024
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Combining knowledge graphs and large language models
Amanda Kau, Xuzeng He, Aishwarya Nambissan, Aland Astudillo, Hui Yin, and Amir Aryani · 2024
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LAB-Bench: Measuring capabilities of language models for biology research, 2024
Jon M. Laurent, Joseph D. Janizek, Michael Ruzo, Michaela M. Hinks, Michael J. Hammerling, Siddharth Narayanan, Manvitha Ponnapati, Andrew D. White, and Samuel G. Rodriques · 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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GNN-RAG: Graph neural retrieval for large language model reasoning
Costas Mavromatis and George Karypis · 2024
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Transcriptome-wide characterization of genetic perturbations
Ajay Nadig, Joseph Replogle, Angela Pogson, Steven Mccarroll, Jonathan Weissman, Elise Robinson, and Luke O’Connor · 2024
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Sequence modeling and design from molecular to genome scale with Evo
Eric Nguyen, Michael Poli, Matthew G Durrant, Brian Kang, Dhruva Katrekar, David B Li, Liam J Bartie, Armin W Thomas, Samuel H King, Garyk Brixi, et al · 2024
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Let your graph do the talking: Encoding structured data for LLMs
Bryan Perozzi, Bahare Fatemi, Dustin Zelle, Anton Tsitsulin, Mehran Kazemi, Rami Al-Rfou, and Jonathan Halcrow · 2024
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CRISPR-GPT: An LLM agent for automated design of gene-editing experiments
Yuanhao Qu, Kaixuan Huang, Henry Cousins, William A Johnson, Di Yin, Mihir Shah, Denny Zhou, Russ Altman, Mengdi Wang, and Le Cong · 2024
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BioDiscoveryAgent: An AI agent for designing genetic perturbation experiments
Yusuf H Roohani, Jian Vora, Qian Huang, Percy Liang, and Jure Leskovec · 2024
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Caduceus: Bi-directional equivariant long-range DNA sequence modeling
Yair Schiff, Chia Hsiang Kao, Aaron Gokaslan, Tri Dao, Albert Gu, and Volodymyr Kuleshov · 2024
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Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, and Karthik Narasimhan · 2024
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Accessing GPT-4 level mathematical olympiad solutions via Monte Carlo tree self-refine with LLaMa-3 8B, 2024
Di Zhang, Xiaoshui Huang, Dongzhan Zhou, Yuqiang Li, and Wanli Ouyang · 2024
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