Results 11 to 20 of about 320,395 (368)

Museum of Spatial Transcriptomics [PDF]

Nature Methods, 2021
AbstractThe function of many biological systems, such as embryos, liver lobules, intestinal villi, and tumors depends on the spatial organization of their cells. In the past decade high-throughput technologies have been developed to quantify gene expression in space, and computational methods have been developed that leverage spatial gene expression ...
Lambda Moses, Lior Pachter
openaire   +7 more sources

Deep generative modeling for single-cell transcriptomics. [PDF]

Nature Methods, 2018
Single-cell transcriptome measurements can reveal unexplored biological diversity, but they suffer from technical noise and bias that must be modeled to account for the resulting uncertainty in downstream analyses.
A Regev, A Tanay, A Wagner, A Zeisel, AP Patel, B Wang, BK Tusi, CA Vallejos, CA Vallejos, D DeTomaso, D Grün, D Risso, DM Blei, E Pierson, FA Wolf, G Finak, G Görgün, GXY Zheng, HI Nakaya, J Ding, J Fan, Jeffrey Regier, JT Gaublomme, K Shekhar, L Haghverdi, L Held, M Stoeckius, MD Robinson, MI Love, Michael B. Cole, Michael I. Jordan, Nir Yosef, PV Kharchenko, Q Li, RE Kass, Romain Lopez, S Prabhakaran, S Semrau, U Shaham, WE Johnson   +39 more
core   +2 more sources

Advances in spatial transcriptomics and its applications in cancer research

Molecular Cancer
Malignant tumors have increasing morbidity and high mortality, and their occurrence and development is a complicate process. The development of sequencing technologies enabled us to gain a better understanding of the underlying genetic and molecular ...
Yang Jin, Yuanli Zuo, Gang Li, Wenrong Liu, Yitong Pan, Ting Fan, Xin Fu, Xiaojun Yao, Yong Peng   +8 more
doaj   +2 more sources

Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

bioRxiv, 2023
Spatial transcriptomics technologies generate gene expression profiles with spatial context, requiring spatially informed analysis tools for three key tasks, spatial clustering, multisample integration, and cell-type deconvolution.
Yahui Long, Kok Siong Ang, Mengwei Li, Kian Long Kelvin Chong, R. Sethi, Chengwei Zhong, Hang Xu, Zhiwei Ong, K. Sachaphibulkij, Ao Chen, Zeng Li, H. Fu, Min Wu, Hsiu Kim Lina Lim, Longqi Liu, Jinmiao Chen   +15 more
semanticscholar   +1 more source

Large Scale Foundation Model on Single-cell Transcriptomics

bioRxiv, 2023
Large-scale pretrained models have become foundation models leading to breakthroughs in natural language processing and related fields. Developing foundation models in life science for deciphering the “languages” of cells and facilitating biomedical ...
Minsheng Hao, Jing Gong, Xin Zeng, Chiming Liu, Yucheng Guo, Xingyi Cheng, Taifeng Wang, Jianzhu Ma, Leo T. Song, Xuegong Zhang   +9 more
semanticscholar   +1 more source

Screening cell–cell communication in spatial transcriptomics via collective optimal transport

Nature Methods, 2023
This work presents a computational framework, COMMOT, to spatially infer cell–cell communication from transcriptomics data based on a variant of optimal transport (OT).
Zixuan Cang, Yanxiang Zhao, Axel A. Almet, Adam R. Stabell, Raul Ramos, M. Plikus, Scott X. Atwood, Qing Nie   +7 more
semanticscholar   +1 more source

Transcriptomics in ecotoxicology [PDF]

Analytical and Bioanalytical Chemistry, 2010
The emergence of analytical tools for high-throughput screening of biomolecules has revolutionized the way in which toxicologists explore the impact of chemicals or other stressors on organisms. One of the most developed and routinely applied high-throughput analysis approaches is transcriptomics, also often referred to as gene expression profiling ...
Danielle J. Madureira, Danielle J. Madureira, Beat B. Fischer, Kristin Schirmer, Kristin Schirmer, Smitha Pillai   +5 more
openaire   +5 more sources

A single–cell type transcriptomics map of human tissues

Science Advances, 2021
Single-cell RNA analysis has been integrated with spatial protein profiling to create a single–cell type map of human tissues. Advances in molecular profiling have opened up the possibility to map the expression of genes in cells, tissues, and organs in ...
Max J. Karlsson, Cheng Zhang, Loren Méar, Wen Zhong, A. Digre, Borbala Katona, E. Sjöstedt, L. Butler, J. Odeberg, P. Dusart, F. Edfors, P. Oksvold, K. von Feilitzen, M. Zwahlen, M. Arif, O. Altay, Xiangyu Li, M. Ozcan, Adil Mardonoglu, Linn Fagerberg, J. Mulder, Yonglun Luo, F. Pontén, M. Uhlén, C. Lindskog   +24 more
semanticscholar   +1 more source

Improving ancient DNA genome assembly [PDF]

PeerJ, 2017
Most reconstruction methods for genomes of ancient origin that are used today require a closely related reference. In order to identify genomic rearrangements or the deletion of whole genes, de novo assembly has to be used.
Alexander Seitz, Kay Nieselt
doaj   +2 more sources

Hot Transcriptomics [PDF]

Archaea, 2010
DNA microarray technology allows for a quick and easy comparison of complete transcriptomes, resulting in improved molecular insight in fluctuations of gene expression. After emergence of the microarray technology about a decade ago, the technique has now matured and has become routine in many molecular biology laboratories.
Walther, J., Sierocinski, P., van der Oost, J.   +2 more
openaire   +3 more sources