Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Caroline Uhler"'
Autor:
Xinyi Zhang, Saradha Venkatachalapathy, Daniel Paysan, Paulina Schaerer, Claudio Tripodo, Caroline Uhler, G. V. Shivashankar
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-16 (2024)
Abstract Ductal carcinoma in situ (DCIS) is a pre-invasive tumor that can progress to invasive breast cancer, a leading cause of cancer death. We generate a large-scale tissue microarray dataset of chromatin images, from 560 samples from 122 female p
Externí odkaz:
https://doaj.org/article/7d7644fe553d46ba91722e856b0dcf58
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-12 (2023)
Abstract Transfer learning refers to the process of adapting a model trained on a source task to a target task. While kernel methods are conceptually and computationally simple models that are competitive on a variety of tasks, it has been unclear ho
Externí odkaz:
https://doaj.org/article/6693eae6e9774fd49bc3f03e13a82242
Autor:
Adityanarayanan Radhakrishnan, Sam F. Friedman, Shaan Khurshid, Kenney Ng, Puneet Batra, Steven A. Lubitz, Anthony A. Philippakis, Caroline Uhler
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-12 (2023)
Abstract A fundamental challenge in diagnostics is integrating multiple modalities to develop a joint characterization of physiological state. Using the heart as a model system, we develop a cross-modal autoencoder framework for integrating distinct
Externí odkaz:
https://doaj.org/article/b40d79696a384ecd99367367a11a9949
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-17 (2022)
Methods for jointly analysing the different spatial data modalities in 3D are lacking. Here the authors report the computational framework STACI (Spatial Transcriptomic data using over-parameterized graph-based Autoencoders with Chromatin Imaging dat
Externí odkaz:
https://doaj.org/article/6669b42e483346558b95c600fef8221c
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-13 (2022)
Abstract Long-term sustained mechano-chemical signals in tissue microenvironment regulate cell-state transitions. In recent work, we showed that laterally confined growth of fibroblasts induce dedifferentiation programs. However, the molecular mechan
Externí odkaz:
https://doaj.org/article/c6d37e2ff2fc4da8a7fe913c747ddf54
Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing
Autor:
Anastasiya Belyaeva, Louis Cammarata, Adityanarayanan Radhakrishnan, Chandler Squires, Karren Dai Yang, G. V. Shivashankar, Caroline Uhler
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-13 (2021)
Given the severity of the SARS-CoV-2 pandemic, a major challenge is to rapidly repurpose existing approved drugs for clinical interventions. Here, the authors identify robust druggable protein targets within a principled causal framework that makes u
Externí odkaz:
https://doaj.org/article/0070bbeebfbc43a1a7a2f2bff257da7c
Autor:
Karren Dai Yang, Anastasiya Belyaeva, Saradha Venkatachalapathy, Karthik Damodaran, Abigail Katcoff, Adityanarayanan Radhakrishnan, G. V. Shivashankar, Caroline Uhler
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-10 (2021)
Integration of single cell data modalities increases the richness of information about the heterogeneity of cell states, but integration of imaging and transcriptomics is an open challenge. Here the authors use autoencoders to learn a probabilistic c
Externí odkaz:
https://doaj.org/article/7df126930d194ef68d3d6f0c6ad92f1f
Autor:
Karren Dai Yang, Karthik Damodaran, Saradha Venkatachalapathy, Ali C Soylemezoglu, G V Shivashankar, Caroline Uhler
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 4, p e1007828 (2020)
Lineage tracing involves the identification of all ancestors and descendants of a given cell, and is an important tool for studying biological processes such as development and disease progression. However, in many settings, controlled time-course ex
Externí odkaz:
https://doaj.org/article/b7da05a4481c4feb92a79275977232c7
Publikováno v:
The Journal of Privacy and Confidentiality, Vol 5, Iss 1 (2013)
Traditional statistical methods for confidentiality protection of statistical databases do not scale well to deal with GWAS databases especially in terms of guarantees regarding protection from linkage to external information. The more recent concept
Externí odkaz:
https://doaj.org/article/c74141074d8b44d891c5a5d5144565ba
Publikováno v:
Proceedings of the National Academy of Sciences. 120
While neural networks are used for classification tasks across domains, a long-standing open problem in machine learning is determining whether neural networks trained using standard procedures are consistent for classification, i.e., whether such mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9239b6c4321e1e3f0a650c16b3ec8d3
https://doi.org/10.1073/pnas.2208779120
https://doi.org/10.1073/pnas.2208779120