Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies
Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs)
are tremendous, the design and discovery of new candidates remain a time and cost …
are tremendous, the design and discovery of new candidates remain a time and cost …
[HTML][HTML] Machine learning for perturbational single-cell omics
Cell biology is fundamentally limited in its ability to collect complete data on cellular
phenotypes and the wide range of responses to perturbation. Areas such as computer vision …
phenotypes and the wide range of responses to perturbation. Areas such as computer vision …
[HTML][HTML] Mapping single-cell data to reference atlases by transfer learning
Large single-cell atlases are now routinely generated to serve as references for analysis of
smaller-scale studies. Yet learning from reference data is complicated by batch effects …
smaller-scale studies. Yet learning from reference data is complicated by batch effects …
Joint probabilistic modeling of single-cell multi-omic data with totalVI
The paired measurement of RNA and surface proteins in single cells with cellular indexing
of transcriptomes and epitopes by sequencing (CITE-seq) is a promising approach to …
of transcriptomes and epitopes by sequencing (CITE-seq) is a promising approach to …
[HTML][HTML] Benchmarking atlas-level data integration in single-cell genomics
Single-cell atlases often include samples that span locations, laboratories and conditions,
leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets …
leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets …
Supervised training of conditional monge maps
Optimal transport (OT) theory describes general principles to define and select, among many
possible choices, the most efficient way to map a probability measure onto another. That …
possible choices, the most efficient way to map a probability measure onto another. That …
[HTML][HTML] Efficient and precise single-cell reference atlas mapping with Symphony
Recent advances in single-cell technologies and integration algorithms make it possible to
construct comprehensive reference atlases encompassing many donors, studies, disease …
construct comprehensive reference atlases encompassing many donors, studies, disease …
[HTML][HTML] Biologically informed deep learning to query gene programs in single-cell atlases
M Lotfollahi, S Rybakov, K Hrovatin… - Nature Cell …, 2023 - nature.com
The increasing availability of large-scale single-cell atlases has enabled the detailed
description of cell states. In parallel, advances in deep learning allow rapid analysis of newly …
description of cell states. In parallel, advances in deep learning allow rapid analysis of newly …
[HTML][HTML] Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells
RNA velocity has been rapidly adopted to guide interpretation of transcriptional dynamics in
snapshot single-cell data; however, current approaches for estimating RNA velocity lack …
snapshot single-cell data; however, current approaches for estimating RNA velocity lack …
Predicting cellular responses to complex perturbations in high‐throughput screens
M Lotfollahi, A Klimovskaia Susmelj… - Molecular systems …, 2023 - embopress.org
Recent advances in multiplexed single‐cell transcriptomics experiments facilitate the high‐
throughput study of drug and genetic perturbations. However, an exhaustive exploration of …
throughput study of drug and genetic perturbations. However, an exhaustive exploration of …