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检索条件"机构=Interdepartmental Program in Bioinformatics"
72 条 记 录,以下是1-10 订阅
排序:
BRAINLM: A FOUNDATION MODEL FOR BRAIN ACTIVITY RECORDINGS  12
BRAINLM: A FOUNDATION MODEL FOR BRAIN ACTIVITY RECORDINGS
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12th International Conference on Learning Representations, ICLR 2024
作者: Caro, Josue Ortega de Fonseca, Antonio H. Rizvi, Syed A. Rosati, Matteo Averill, Christopher Cross, James L. Mittal, Prateek Zappala, Emanuele Dhodapkar, Rahul M. Abdallah, Chadi G. van Dijk, David Wu Tsai Institute United States Interdepartmental Neuroscience Program Yale University United States Baylor College of Medicine United States Department of Computer Science United States Yale School of Medicine United States University of Southern California United States Interdepartmental Program in Computational Biology & Bioinformatics United States Internal Medicine United States Cardiovascular Research Center Yale University United States Department of Mathematics and Statistics Idaho State University United States
We introduce the Brain Language Model (BrainLM), a foundation model for brain activity dynamics trained on 6,700 hours of fMRI recordings. Utilizing self-supervised masked-prediction training, BrainLM demonstrates pro... 详细信息
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Hyperbolic Diffusion Procrustes Analysis for Intrinsic Representation of Hierarchical Data Sets
Hyperbolic Diffusion Procrustes Analysis for Intrinsic Repre...
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Ya-Wei Eileen Lin Yuval Kluger Ronen Talmon Viterbi Faculty of Electrical and Computer Engineering Technion Interdepartmental Program in Computational Biology and Bioinformatics Yale University Applied Math Program Yale University Department of Pathology School of Medicine Yale University
In this paper, we present Hyperbolic Diffusion Procrustes Analysis (HDPA), a new method for informative representation of hierarchical datasets based on hyperbolic geometry, diffusion geometry, and Procrustes analysis...
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Entropic Optimal Transport Eigenmaps for Nonlinear Alignment and Joint Embedding of High-Dimensional Datasets
arXiv
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arXiv 2024年
作者: Landa, Boris Kluger, Yuval Ma, Rong Department of Electrical Engineering Yale University United States Program in Applied Mathematics Yale University United States Department of Biostatistics Harvard University United States Interdepartmental Program in Computational Biology and Bioinformatics Yale University United States Department of Pathology Yale University School of Medicine United States
Embedding high-dimensional data into a low-dimensional space is an indispensable component of data analysis. In numerous applications, it is necessary to align and jointly embed multiple datasets from different studie... 详细信息
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Pre-Training Genomic Language Model with Variants for Better Modeling Functional Genomics
SSRN
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SSRN 2025年
作者: Liu, Tianyu Zhang, Xiangyu Ying, Rex Zhao, Hongyu Interdepartmental Program in Computational Biology & Bioinformatics Yale University New HavenCT06511 United States Department of Biostatistics Yale University New HavenCT06511 United States Department of Computer Science Yale University New HavenCT06511 United States
Sequence-to-function models can predict gene expression from sequence data and be used to link genetic information with transcriptomics data to understand regulatory processes and their effects on complex phenotypes. ... 详细信息
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Continuous Spatiotemporal Transformers
arXiv
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arXiv 2023年
作者: de Oliveira Fonseca, Antonio Henrique Zappala, Emanuele Caro, Josue Ortega van Dijk, David Interdepartmental Neuroscience Program Yale University New HavenCT United States Department of Computer Science Yale University New HavenCT United States Department of Neuroscience Yale University New HavenCT United States Wu Tsai Institute Yale University New HavenCT United States Yale University New HavenCT United States Interdepartmental Program in Computational Biology & Bioinformatics Yale University New HavenCT United States
Modeling spatiotemporal dynamical systems is a fundamental challenge in machine learning. Transformer models have been very successful in NLP and computer vision where they provide interpretable representations of dat... 详细信息
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APIR:Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control
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Genomics, Proteomics & bioinformatics 2024年 第2期22卷 171-187页
作者: Yiling Elaine Chen Xinzhou Ge Kyla Woyshner MeiLu McDermott Antigoni Manousopoulou Scott B.Ficarro Jarrod A.Marto Kexin Li Leo David Wang Jingyi Jessica Li Department of Statistics and Data Science University of CaliforniaLos AngelesCA 90095USA Department of Immuno-Oncology Beckman Research InstituteCity of Hope National Medical CenterDuarteCA 91010USA Department of Quantitative and Computational Biology University of Southern CaliforniaLos AngelesCA 90089USA Department of Cancer Biology and Blais Proteomics Center Dana-Farber Cancer InstituteDepartment of PathologyBrigham and Women’s Hospital and Harvard Medical SchoolBostonMA 02215USA Department of Pediatrics City of Hope National Medical CenterDuarteCA 91010USA Bioinformatics Interdepartmental Program University of CaliforniaLos AngelesCA 90095USA Department of Human Genetics University of CaliforniaLos AngelesCA 90095USA Department of Computational Medicine University of CaliforniaLos AngelesCA 90095USA Department of Biostatistics University of CaliforniaLos AngelesCA 90095USA
Advances in mass spectrometry(MS)have enabled high-throughput analysis of proteomes in biological *** state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide... 详细信息
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Learning Multi-cellular Representations of Single-Cell Transcriptomics Data Enables Characterization of Patient-Level Disease States  29th
Learning Multi-cellular Representations of Single-Cell Tran...
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29th International Conference on Research in Computational Molecular Biology, RECOMB 2025
作者: Liu, Tianyu De Brouwer, Edward Kuo, Tony Diamant, Nathaniel Missarova, Alsu Wang, Hanchen Hao, Minsheng Bravo, Hector Corrada Scalia, Gabriele Regev, Aviv Heimberg, Graham Research and Early Development Genentech South San FranciscoCA94080 United States Interdepartmental Program in Computational Biology and Bioinformatics Yale University New HavenCT06511 United States Roche Informatics F. Hoffmann-La Roche Ltd. Mississauga Canada Department of Computer Science Stanford University Palo AltoCA94035 United States
Single-cell RNA-seq (scRNA-seq) has become a prominent tool for studying human biology and disease. The availability of massive scRNA-seq datasets and advanced machine learning techniques has recently driven the devel... 详细信息
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Multifaceted role of RNA editing in promoting loss-of-function of PODXL in cancer
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iScience 2022年 第8期25卷 104836页
作者: Fu, Ting Chan, Tracey W. Bahn, Jae Hoon Kim, Tae-Hyung Rowat, Amy C. Xiao, Xinshu Molecular Cellular and Integrative Physiology Interdepartmental Program University of California Los Angeles Los Angeles 90095 CA United States Bioinformatics Interdepartmental Program University of California Los Angeles Los Angeles 90095 CA United States Department of Integrative Biology and Physiology University of California Los Angeles Los Angeles 90095 CA United States
PODXL, a protein that is dysregulated in multiple cancers, plays an important role in promoting cancer metastasis. In this study, we report that RNA editing promotes the inclusion of a PODXL alternative exon. The resu... 详细信息
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Hyperbolic procrustes analysis using riemannian geometry  21
Hyperbolic procrustes analysis using riemannian geometry
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Proceedings of the 35th International Conference on Neural Information Processing Systems
作者: Ya-Wei Eileen Lin Yuval Kluger Ronen Talmon Viterbi Faculty of Electrical and Computer Engineering Technion Program in Applied Mathematics Yale University and Interdepartmental Program in Computational Biology and Bioinformatics Yale University and Department of Pathology Yale University
Label-free alignment between datasets collected at different times, locations, or by different instruments is a fundamental scientific task. Hyperbolic spaces have recently provided a fruitful foundation for the devel...
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Synthetic Control Removes Spurious Discoveries from Double Dipping in Single-Cell and Spatial Transcriptomics Data Analyses  29th
Synthetic Control Removes Spurious Discoveries from Double ...
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29th International Conference on Research in Computational Molecular Biology, RECOMB 2025
作者: Song, Dongyuan Chen, Siqi Lee, Christy Li, Kexin Ge, Xinzhou Li, Jingyi Jessica Department of Genetics and Genome Sciences University of Connecticut Health Center FarmingtonCT06032 United States Interdepartmental Program of Bioinformatics University of California Los Angeles Los AngelesCA90095-7246 United States Department of Statistics and Data Science University of California Los Angeles Los AngelesCA90095-1554 United States Department of Statistics Oregon State University CorvallisOR97331-4606 United States
Double dipping is a common analytical pitfall in single-cell and spatial transcriptomics data analysis: after a clustering algorithm finds clusters as putative cell types or spatial domains, statistical tests are appl... 详细信息
来源: 评论