Results 41 to 50 of about 407,505 (399)

scGPT: toward building a foundation model for single-cell multi-omics using generative AI

Nature Methods
Generative pretrained models have achieved remarkable success in various domains such as language and computer vision. Specifically, the combination of large-scale diverse datasets and pretrained transformers has emerged as a promising approach for ...
Haotian Cui, Chloe Wang, Hassaan Maan, Kuan Pang, Fengning Luo, Nan Duan, Bo Wang   +6 more
semanticscholar   +1 more source

Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli. [PDF]

, 2016
A significant obstacle in training predictive cell models is the lack of integrated data sources. We develop semi-supervised normalization pipelines and perform experimental characterization (growth, transcriptional, proteome) to create Ecomics, a ...
Kim, Minseung, Rai, Navneet, Tagkopoulos, Ilias, Zorraquino, Violeta   +3 more
core   +2 more sources

Omics of Cancer

Asian Pacific Journal of Cancer Prevention, 2012
With the advances in modern diagnostic expertise for cancer, certain approaches allowing scanning of the complete genome and the proteome are becoming very useful for researchers. These high throughput techniques have already proven power, over traditional detection methods, in differentiating disease sub-types and identifying specific genetic events ...
Aniruddha, Bhati, H, Garg, A, Gupta, H, Chhabra, A, Kumari, T, Patel   +5 more
openaire   +3 more sources

Think big — think omics [PDF]

Journal of Inherited Metabolic Disease, 2018
Traditionally the laboratory diagnosis of inborn errors of metabolism largely relies on targeted hypothesis‐driven measurements of metabolites in body fluids. The hypothesis is usually based on the phenotypic characteristics of the patient, defined through deep phenotyping or phenomics.
Wevers, Ron A, Blau, Nenad
openaire   +4 more sources

Mapping mammalian cell-type-specific transcriptional regulatory networks using KD-CAGE and ChIP-seq data in the TC-YIK cell line.

Frontiers in Genetics, 2015
Mammals are composed of hundreds of different cell types with specialized functions. Each of these cellular phenotypes are controlled by different combinations of transcription factors.
Marina eLizio, Marina eLizio, Yuri eIshizu, Yuri eIshizu, Masayoshi eItoh, Masayoshi eItoh, Masayoshi eItoh, Timo eLassmann, Timo eLassmann, Akira eHasegawa, Akira eHasegawa, Atsutaka eKubosaki, Jessica eSeverin, Jessica eSeverin, Hideya eKawaji, Hideya eKawaji, Hideya eKawaji, Yukio eNakamura, Harukazu eSuzuki, Harukazu eSuzuki, Yoshihide eHayashizaki, Yoshihide eHayashizaki, Piero eCarninci, Piero eCarninci, Alistair R R Forrest, Alistair R R Forrest, Alistair R R Forrest   +26 more
doaj   +1 more source

Bridging the gap between omics and earth system science to better understand how environmental change impacts marine microbes [PDF]

, 2015
The advent of genomic-, transcriptomic- and proteomic-based approaches has revolutionized our ability to describe marine microbial communities, including biogeography, metabolic potential and diversity, mechanisms of adaptation, and phylogeny and ...
Alexander, Allen, Alvain, Ashworth, Baas-Becking, Bach, Barton, Behrenfeld, Behrenfeld, Behrenfeld, Bennett, Bihan, Bochdanovits, Bopp, Bowler, Boyd, Boyd, Boyle, Bruggeman, Buitenhuis, Buitenhuis, Buitenhuis, Button, Chappell, Coesel, Coleman, Collins, Corellou, Daines, Davis, Delong, Derelle, Deutsch, Dinsdale, Djouani-Tahri el, Doney, Draghi, Dufresne, Dutkiewicz, Edwards, Elena, Fabris, Follows, Follows, Franklin, Ghiglione, Gilbert, Gould, Hartmann, Hashioka, Hickman, Hillebrand, Hindle, Hof, Hood, House, Hutchins, Huysman, Hüner, Johnson, Juhas, Juranek, Kashtan, Kim, Kiorboe, Knoop, Kroeker, Krumholz, Ladau, Lanfear, Langer, Laws, Ley, Lindell, Litchman, Litchman, Loeuille, Lohbeck, Luo, Marchetti, Marinov, Martiny, Masotti, McKew, Mock, Monnier, Monteiro, Moore, Moulager, O'Neill, Oschlies, Patel, Piotrowski, Plummer, Poloczanaska, Quere, Raes, Ral, Raven, Raven, Raymond, Reed, Ridgwell, Riley, Rocap, Saito, Schaum, Schlichting, Schmidt, Shuter, Smetacek, Sorokina, Steuer, Stramma, Talmy, Taucher, Taylor, Thomas, Toseland, Traylor-Knowles, Troein, Vallino, Veluchamy, Via, Vogt, Vu, Webb, Wecker, Wijffels, Zinser   +129 more
core   +1 more source

MONET: Multi-omic module discovery by omic selection

PLOS Computational Biology, 2020
Recent advances in experimental biology allow creation of datasets where several genome-wide data types (called omics) are measured per sample. Integrative analysis of multi-omic datasets in general, and clustering of samples in such datasets specifically, can improve our understanding of biological processes and discover different disease subtypes. In
Nimrod Rappoport, Roy Safra, Ron Shamir
openaire   +4 more sources

Interplay between circadian and other transcription factors—Implications for cycling transcriptome reprogramming

FEBS Letters, EarlyView.
This perspective highlights emerging insights into how the circadian transcription factor CLOCK:BMAL1 regulates chromatin architecture, cooperates with other transcription factors, and coordinates enhancer dynamics. We propose an updated framework for how circadian transcription factors operate within dynamic and multifactorial chromatin landscapes ...
Xinyu Y. Nie, Jerome S. Menet
wiley   +1 more source

Nonlinear dynamics of multi-omics profiles during human aging

Nature Aging
Aging is a complex process associated with nearly all diseases. Understanding the molecular changes underlying aging and identifying therapeutic targets for aging-related diseases are crucial for increasing healthspan. Although many studies have explored
Xiaotao Shen, Chuchu Wang, Xin Zhou, Wenyu Zhou, Daniel Hornburg, Si Wu, M. Snyder   +6 more
semanticscholar   +1 more source

Sex Age Annotated omics Data: Enabling powerful omics studies

, 2023
There is increasing evidence that many molecular processes exhibit differences with age 1 and sex. Such differences produces also differences in the insurgence and progression of many 2 complex diseases. For instances, demographic data on insurgence of comorbidities of mellitus 3 diabetes, on lethality of COVID-19, and on some cancers, shows ...
Pietro Hiram Guzzi, Francesca Cortese, Raffaele Giancotti, Ugo Lomoio, Barbara Puccio, Patrizia Vizza, Giuseppe Tradigo, Pierangelo Veltri   +7 more
openaire   +1 more source