Results 71 to 80 of about 7,457,987 (378)
Function‐driven design of a surrogate interleukin‐2 receptor ligand
FEBS Letters, EarlyView.Interleukin (IL)‐2 signaling can be achieved and precisely fine‐tuned through the affinity, distance, and orientation of the heterodimeric receptors with their ligands. We designed a biased IL‐2 surrogate ligand that selectively promotes effector T and natural killer cell activation and differentiation. Interleukin (IL) receptors play a pivotal role in
Ziwei Tang +9 more
wiley +1 more source
Defining functional distances over Gene Ontology
BMC Bioinformatics, 2008 Background A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-structured ontologies exist regarding the activity of proteins (i.e.
del Pozo Angela +2 more
doaj +1 more source
FEBS Letters, EarlyView.Bone metastasis in prostate cancer (PCa) patients is a clinical hurdle due to the poor understanding of the supportive bone microenvironment. Here, we identify stearoyl‐CoA desaturase (SCD) as a tumor‐promoting enzyme and potential therapeutic target in bone metastatic PCa.
Alexis Wilson +7 more
wiley +1 more source
MEGO: gene functional module expression based on gene ontology
BioTechniques, 2005 Existing analysis tools to study the collective properties of gene functional modules cannot return highly homogeneous modules and do not provide quantitative measures of module activity level.
Kang Tu, Hui Yu, Mingzhu Zhu
doaj +1 more source
GOnet: a tool for interactive Gene Ontology analysis
BMC Bioinformatics, 2018 Biological interpretation of gene/protein lists resulting from -omics experiments can be a complex task. A common approach consists of reviewing Gene Ontology (GO) annotations for entries in such lists and searching for enrichment patterns. Unfortunately,
M. Pomaznoy, Brendan Ha, Bjoern Peters
semanticscholar +1 more source
PREDICTING GENE FUNCTION FROM GENE EXPRESSIONS AND ONTOLOGIES [PDF]
Biocomputing 2001, 2000 We introduce a methodology for inducing predictive rule models for functional classification of gene expressions from microarray hybridisation experiments. The basic learning method is the rough set framework for rule induction. The methodology is different from the commonly used unsupervised clustering approaches in that it exploits background ...
T R, Hvidsten +3 more
openaire +2 more sources
Molecular Oncology, EarlyView.AZD9291 has shown promise in targeted cancer therapy but is limited by resistance. In this study, we employed metabolic labeling and LC–MS/MS to profile time‐resolved nascent protein perturbations, allowing dynamic tracking of drug‐responsive proteins. We demonstrated that increased NNMT expression is associated with drug resistance, highlighting NNMT ...
Zhanwu Hou +5 more
wiley +1 more source
The Gene Ontology: enhancements for 2011 [PDF]
, 2012 The Gene Ontology (GO) (http://www.geneontology.org) is a community bioinformatics resource that represents gene product function through the use of structured, controlled vocabularies.
Chan, J. +3 more
core
Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways
PLoS ONE, 2017 Identifying essential genes in a given organism is important for research on their fundamental roles in organism survival. Furthermore, if possible, uncovering the links between core functions or pathways with these essential genes will further help us ...
Lei Chen +5 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.This study indicates that Merkel cell carcinoma (MCC) does not originate from Merkel cells, and identifies gene, protein & cellular expression of immune‐linked and neuroendocrine markers in primary and metastatic Merkel cell carcinoma (MCC) tumor samples, linked to Merkel cell polyomavirus (MCPyV) status, with enrichment of B‐cell and other immune cell
Richie Jeremian +10 more
wiley +1 more source