Results 231 to 240 of about 784,733 (395)

Quantitative Proteomics of the Cancer Cell Line Encyclopedia

Cell, 2020
David P. Nusinow, John Szpyt, M. Ghandi, Christopher M. Rose, E. McDonald, M. Kalocsay, Judit Jané-Valbuena, Ellen T. Gelfand, Devin K. Schweppe, Mark P. Jedrychowski, J. Golji, D. Porter, T. Rejtar, Y. K. Wang, G. Kryukov, F. Stegmeier, B. Erickson, Levi A. Garraway, Levi A. Garraway, W. Sellers, S. Gygi   +20 more
semanticscholar   +1 more source

Increasing the throughput of sensitive proteomics by plexDIA

bioRxiv, 2021
Jason Derks, Andrew Leduc, Georg Wallmann, R. Gray Huffman, M. Willetts, Saad Khan, Harrison Specht, M. Ralser, V. Demichev, N. Slavov   +9 more
semanticscholar   +1 more source

GDC: Integration of Multi‐Omic and Phenotypic Resources to Unravel the Genetic Pathogenesis of Hearing Loss

Advanced Science, EarlyView.
Overview of the Genetic Deafness Commons (GDC), integrating data from the Chinese Deafness Genetics Consortium (CDGC) and 51 public databases. The GDC provides tools for variant search, functional predictions, and gene‐disease visualization, offering insights into 201 hearing loss genes and facilitating novel gene discovery and clinical applications ...
Hui Cheng, Xuegang Wang, Mingjun Zhong, Jia Geng, Wenjian Li, Kanglu Pei, Jing Wang, Lanchen Wang, Yu Lu, Jing Cheng, Fengxiao Bu, Huijun Yuan   +11 more
wiley   +1 more source

Refining Platelet Purification Methods: Enhancing Proteomics for Clinical Applications [PDF]

arXiv
Background: Platelet proteomics offers valuable insights for clinical research, yet isolating high-purity platelets remains a challenge. Current methods often lead to contamination or platelet loss, compromising data quality and reproducibility. Objectives: This study aimed to optimize a platelet isolation technique that yields high-purity samples ...
arxiv  

Ultra-fast proteomics with Scanning SWATH

Nature Biotechnology, 2021
Christoph B. Messner, V. Demichev, N. Bloomfield, Jason S. L. Yu, M. White, Marco Kreidl, Anna-Sophia Egger, A. Freiwald, Gordana Ivosev, Fras Wasim, Aleksej Zelezniak, Linda Jürgens, N. Suttorp, L. Sander, F. Kurth, K. Lilley, M. Mülleder, S. Tate, M. Ralser   +18 more
semanticscholar   +1 more source

New Drug Discovery in the Postgenomic Era: From Genomics to Proteomics

, 2000
Stephen M. Stahl
openalex   +2 more sources

Proteomic Analysis of Arabidopsis Seed Germination and Priming [PDF]

, 2001
Karine Gallardo, Claudette Job, S.P.C. Groot, Magda Puype, Hans Demol, Joël Vandekerckhove, Dominique Job   +6 more
openalex   +1 more source

Microbiome Single Cell Atlases Generated with a Commercial Instrument

Advanced Science, EarlyView.
Single cell sequencing is valuable for dissecting complex systems and uncovering unique features in individual cell types. However, tools for single cell microbial analysis are limited. Easily Accessible Single microbe sequencing (EASi‐seq), which adapts a commercially available single cell platform for efficient sequencing of single microbial genomes ...
Xiangpeng Li, Linfeng Xu, Benjamin Demaree, Cecilia Noecker, Jordan E. Bisanz, Daniel W. Weisgerber, Cyrus Modavi, Peter J. Turnbaugh, Adam R. Abate   +8 more
wiley   +1 more source

Proteomics [PDF]

Nature Biotechnology, 2019
openaire   +2 more sources

Accurate Transcription Factor Activity Inference to Decipher Cell Identity from Single‐Cell Transcriptomic Data with MetaTF

Advanced Science, EarlyView.
MetaTF is a new computational framework that uses single‐cell RNA sequencing (scRNA‐seq) data to infer transcription factor activity with the aim to help in deciphering cells identity starting from a heterogeneous population, and apply it to characterize mouse hematopoietic stem cells and breast cancer epithelial cells, thus identifying a novel subset ...
Yongfei Hu, Yuanyuan Zhu, Guangjue Tang, Ming Shan, Puwen Tan, Ying Yi, Xiyuan Zhang, Man Liu, Xinyu Li, Le Wu, Jia Chen, Hailong Zheng, Yan Huang, Zhuan Li, Xiaobo Li, Dong Wang   +15 more
wiley   +1 more source