医学 AI - arXivDaily 专题

2411.00801 2024-11-05 q-bio.BM cs.LG 60%

A Heterogeneous Network-based Contrastive Learning Approach for Predicting Drug-Target Interaction

Junwei Hu, Michael Bewong, Selasi Kwashie, Wen Zhang, Vincent M. Nofong, Guangsheng Wu, Zaiwen Feng

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

2410.22949 2024-10-31 cs.LG q-bio.BM 60%

MutaPLM: Protein Language Modeling for Mutation Explanation and Engineering

Yizhen Luo, Zikun Nie, Massimo Hong, Suyuan Zhao, Hao Zhou, Zaiqing Nie

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments NeurIPS 2024 poster

2410.16302 2024-10-23 q-bio.BM cs.LG 60%

Computational design of target-specific linear peptide binders with TransformerBeta

Haowen Zhao, Francesco A. Aprile, Barbara Bravi

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

2409.11654 2024-10-15 q-bio.QM cs.AI cs.LG q-bio.NC 60%

How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities

Charlotte Bunne, Yusuf Roohani, Yanay Rosen, Ankit Gupta, Xikun Zhang, Marcel Roed, Theo Alexandrov, Mohammed AlQuraishi, Patricia Brennan, Daniel B. Burkhardt, Andrea Califano, Jonah Cool, Abby F. Dernburg, Kirsty Ewing, Emily B. Fox, Matthias Haury, Amy E. Herr, Eric Horvitz, Patrick D. Hsu, Viren Jain, Gregory R. Johnson, Thomas Kalil, David R. Kelley, Shana O. Kelley, Anna Kreshuk, Tim Mitchison, Stephani Otte, Jay Shendure, Nicholas J. Sofroniew, Fabian Theis, Christina V. Theodoris, Srigokul Upadhyayula, Marc Valer, Bo Wang, Eric Xing, Serena Yeung-Levy, Marinka Zitnik, Theofanis Karaletsos, Aviv Regev, Emma Lundberg, Jure Leskovec, Stephen R. Quake

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

2402.08790 2024-10-10 cs.LG q-bio.QM 60%

Improving Molecule Generation and Drug Discovery with a Knowledge-enhanced Generative Model

Aditya Malusare, Vaneet Aggarwal

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments Accepted for publication at IEEE/ACM Transactions on Computational Biology and Bioinformatics

2409.20026 2024-10-01 q-bio.QM eess.SP 60%

The EAVI EMG/EEG Board: Hybrid physiological sensing

Atau Tanaka, David Fierro, Francesco Di Maggio, Martin Klang, Stephen Whitmarsh

专题命中生物医学文本：biomedical(abstract)；分类 q-bio、eess.SP

Comments NIME 2023, NIME - New Interfaces for Musical Expression, May 2023, Mexico CIty, Mexico

2409.16327 2024-09-26 q-bio.QM cs.LG 60%

GATher: Graph Attention Based Predictions of Gene-Disease Links

David Narganes-Carlon, Anniek Myatt, Mani Mudaliar, Daniel J. Crowther

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

2407.11435 2024-09-24 q-bio.GN cs.LG stat.ML 60%

Genomic Language Models: Opportunities and Challenges

Gonzalo Benegas, Chengzhong Ye, Carlos Albors, Jianan Canal Li, Yun S. Song

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments Review article; 26 pages, 3 figures, 1 table

2409.04481 2024-09-10 q-bio.QM cs.AI cs.LG 60%

Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trials

Yizhen Zheng, Huan Yee Koh, Maddie Yang, Li Li, Lauren T. May, Geoffrey I. Webb, Shirui Pan, George Church

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

2406.14307 2024-07-03 q-bio.GN cs.CL cs.CV 60%

QuST-LLM: Integrating Large Language Models for Comprehensive Spatial Transcriptomics Analysis

Chao Hui Huang

专题命中生物医学文本：biomedical(abstract)；分类 cs.CV、q-bio

Comments 12 pages, 7 figures

2311.12410 2024-07-01 cs.CL cs.AI cs.LG q-bio.QM 60%

nach0: Multimodal Natural and Chemical Languages Foundation Model

Micha Livne, Zulfat Miftahutdinov, Elena Tutubalina, Maksim Kuznetsov, Daniil Polykovskiy, Annika Brundyn, Aastha Jhunjhunwala, Anthony Costa, Alex Aliper, Alán Aspuru-Guzik, Alex Zhavoronkov

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments Accepted to Chemical Science Journal. Models are publicly available via https://huggingface.co/insilicomedicine/nach0_base and https://huggingface.co/insilicomedicine/nach0_large

Journal ref Chemical Science, 15(22), 8380-8389, 2024

2406.14442 2024-06-24 cs.LG cs.AI cs.CE q-bio.BM q-bio.MN 60%

Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease

Elisa Gómez de Lope, Saurabh Deshpande, Ramón Viñas Torné, Pietro Liò, Enrico Glaab, Stéphane P. A. Bordas

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments Submitted to Machine Learning in Computational Biology 2024 as an extended abstract, 2 pages + 1 appendix

2406.09841 2024-06-17 cs.LG q-bio.BM 60%

Learning Multi-view Molecular Representations with Structured and Unstructured Knowledge

Yizhen Luo, Kai Yang, Massimo Hong, Xing Yi Liu, Zikun Nie, Hao Zhou, Zaiqing Nie

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments 12 pages, 4 figures

2405.09886 2024-05-17 cs.LG cs.AI q-bio.BM 60%

MTLComb: multi-task learning combining regression and classification tasks for joint feature selection

Han Cao, Sivanesan Rajan, Bianka Hahn, Ersoy Kocak, Daniel Durstewitz, Emanuel Schwarz, Verena Schneider-Lindner

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments 33 pages, 3 figures, 5 tables

2405.02354 2024-05-07 cs.LG cs.AI q-bio.QM 60%

Heterogeneous network and graph attention auto-encoder for LncRNA-disease association prediction

Jin-Xing Liu, Wen-Yu Xi, Ling-Yun Dai, Chun-Hou Zheng, Ying-Lian Gao

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments 10 pages, 8 figures

2401.06151 2024-01-15 q-bio.BM cs.AI cs.LG q-bio.QM 60%

Towards Joint Sequence-Structure Generation of Nucleic Acid and Protein Complexes with SE(3)-Discrete Diffusion

Alex Morehead, Jeffrey Ruffolo, Aadyot Bhatnagar, Ali Madani

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments 15 pages, 11 figures, presented at the NeurIPS 2023 Machine Learning in Structural Biology (MLSB) workshop. Code available at https://github.com/Profluent-Internships/MMDiff

2311.17104 2023-12-18 cs.LG cs.AI q-bio.MN 60%

Single-Cell Deep Clustering Method Assisted by Exogenous Gene Information: A Novel Approach to Identifying Cell Types

Dayu Hu, Ke Liang, Hao Yu, Xinwang Liu

专题命中生物医学文本：diagnosis(abstract)；分类 cs.LG、q-bio

2311.09596 2023-11-17 q-bio.BM cs.LG cs.SI 60%

Generating Drug Repurposing Hypotheses through the Combination of Disease-Specific Hypergraphs

Ayush Jain, Marie Laure-Charpignon, Irene Y. Chen, Anthony Philippakis, Ahmed Alaa

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments Extended Abstract presented at Machine Learning for Health (ML4H) symposium 2023, December 10th, 2023, New Orleans, United States, 9 pages

2310.09561 2023-10-17 cs.LG cs.AI q-bio.GN 60%

Graph Neural Network approaches for single-cell data: A recent overview

Konstantinos Lazaros, Dimitris E. Koumadorakis, Panagiotis Vlamos, Aristidis G. Vrahatis

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

2310.09441 2023-10-17 cs.CV physics.bio-ph q-bio.QM 60%

MEMTRACK: A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments

Medha Sawhney, Bhas Karmarkar, Eric J. Leaman, Arka Daw, Anuj Karpatne, Bahareh Behkam

专题命中生物医学文本：biomedical(abstract)；分类 cs.CV、q-bio

2310.02275 2023-10-05 cs.LG q-bio.GN 60%

MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data

Tianyu Liu, Yuge Wang, Rex Ying, Hongyu Zhao

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments Accepted by NeurIPS 2023

2309.03033 2023-09-26 cs.LG q-bio.QM 60%

Deep Learning for Polycystic Kidney Disease: Utilizing Neural Networks for Accurate and Early Detection through Gene Expression Analysis

Kapil Panda, Anirudh Mazumder

专题命中生物医学文本：diagnosis(abstract)；分类 cs.LG、q-bio

Comments 7 pages, 5 figures

2309.01384 2023-09-06 q-bio.QM cs.SY eess.IV eess.SY 60%

Deep Learning Approach for Large-Scale, Real-Time Quantification of Green Fluorescent Protein-Labeled Biological Samples in Microreactors

Yuanyuan Wei, Sai Mu Dalike Abaxi, Nawaz Mehmood, Luoquan Li, Fuyang Qu, Guangyao Cheng, Dehua Hu, Yi-Ping Ho, Scott Wu Yuan, Ho-Pui Ho

专题命中生物医学文本：biomedical(abstract)；分类 q-bio、eess.IV

Comments 23 pages, 6 figures, 1 table

2108.11674 2023-07-31 cs.AI cs.LG q-bio.MN 60%

Graph-guided random forest for gene set selection

Bastian Pfeifer, Hubert Baniecki, Anna Saranti, Przemyslaw Biecek, Andreas Holzinger

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Journal ref Sci Rep 12, 16857 (2022)

2306.09187 2023-06-16 q-bio.BM cs.AI cs.LG 60%

MolCAP: Molecular Chemical reActivity pretraining and prompted-finetuning enhanced molecular representation learning

Yu Wang, JingJie Zhang, Junru Jin, Leyi Wei

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

2306.05257 2023-06-09 cs.LG q-bio.QM 60%

Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction

Xuan Lin, Lichang Dai, Yafang Zhou, Zu-Guo Yu, Wen Zhang, Jian-Yu Shi, Dong-Sheng Cao, Li Zeng, Haowen Chen, Bosheng Song, Philip S. Yu, Xiangxiang Zeng

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments Accepted by Briefings in Bioinformatics

2306.03109 2023-06-07 q-bio.QM cs.LG physics.chem-ph 60%

Machine Learning Force Fields with Data Cost Aware Training

Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

2306.02532 2023-06-06 cs.LG cs.AI q-bio.QM 60%

R-Mixup: Riemannian Mixup for Biological Networks

Xuan Kan, Zimu Li, Hejie Cui, Yue Yu, Ran Xu, Shaojun Yu, Zilong Zhang, Ying Guo, Carl Yang

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

Comments Accepted to KDD 2023

2305.18410 2023-05-31 cs.LG cs.CL q-bio.GN stat.ME 60%

Understanding Breast Cancer Survival: Using Causality and Language Models on Multi-omics Data

Mugariya Farooq, Shahad Hardan, Aigerim Zhumbhayeva, Yujia Zheng, Preslav Nakov, Kun Zhang

专题命中生物医学文本：biomedical(abstract)；分类 cs.LG、q-bio

2305.17183 2023-05-30 q-bio.QM cs.AI eess.IV 60%

ProGroTrack: Deep Learning-Assisted Tracking of Intracellular Protein Growth Dynamics

Kai San Chan, Huimiao Chen, Chenyu Jin, Yuxuan Tian, Dingchang Lin

专题命中生物医学文本：biomedical(abstract)；分类 q-bio、eess.IV

1. 生物医学文本 4507 篇

A Heterogeneous Network-based Contrastive Learning Approach for Predicting Drug-Target Interaction

MutaPLM: Protein Language Modeling for Mutation Explanation and Engineering

Computational design of target-specific linear peptide binders with TransformerBeta

How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities

Improving Molecule Generation and Drug Discovery with a Knowledge-enhanced Generative Model

The EAVI EMG/EEG Board: Hybrid physiological sensing

GATher: Graph Attention Based Predictions of Gene-Disease Links

Genomic Language Models: Opportunities and Challenges

Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trials

QuST-LLM: Integrating Large Language Models for Comprehensive Spatial Transcriptomics Analysis

nach0: Multimodal Natural and Chemical Languages Foundation Model

Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease

Learning Multi-view Molecular Representations with Structured and Unstructured Knowledge

MTLComb: multi-task learning combining regression and classification tasks for joint feature selection

Heterogeneous network and graph attention auto-encoder for LncRNA-disease association prediction

Towards Joint Sequence-Structure Generation of Nucleic Acid and Protein Complexes with SE(3)-Discrete Diffusion

Single-Cell Deep Clustering Method Assisted by Exogenous Gene Information: A Novel Approach to Identifying Cell Types

Generating Drug Repurposing Hypotheses through the Combination of Disease-Specific Hypergraphs

Graph Neural Network approaches for single-cell data: A recent overview

MEMTRACK: A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments

MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data

Deep Learning for Polycystic Kidney Disease: Utilizing Neural Networks for Accurate and Early Detection through Gene Expression Analysis

Deep Learning Approach for Large-Scale, Real-Time Quantification of Green Fluorescent Protein-Labeled Biological Samples in Microreactors

Graph-guided random forest for gene set selection

MolCAP: Molecular Chemical reActivity pretraining and prompted-finetuning enhanced molecular representation learning

Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction

Machine Learning Force Fields with Data Cost Aware Training

R-Mixup: Riemannian Mixup for Biological Networks

Understanding Breast Cancer Survival: Using Causality and Language Models on Multi-omics Data

ProGroTrack: Deep Learning-Assisted Tracking of Intracellular Protein Growth Dynamics