Results 81 to 90 of about 15,541,955 (379)
Physical Constraints and Functional Characteristics of Transcription Factor-DNA Interaction [PDF]
We study theoretical ``design principles'' for transcription factor-DNA interaction in bacteria, focusing particularly on the statistical interaction of the transcription factors (TF's) with the genomic background (i.e., the genome without the target ...
Berg+24 more
core +3 more sources
Single‐cell insights into the role of T cells in B‐cell malignancies
Single‐cell technologies have transformed our understanding of T cell–tumor cell interactions in B‐cell malignancies, revealing new T‐cell subsets, functional states, and immune evasion mechanisms. This Review synthesizes these findings, highlighting the roles of T cells in pathogenesis, progression, and therapy response, and underscoring their ...
Laura Llaó‐Cid
wiley +1 more source
Exposure to common noxious agents (1), including allergens, pollutants, and micro‐nanoplastics, can cause epithelial barrier damage (2) in our body's protective linings. This may trigger an immune response to our microbiome (3). The epithelial barrier theory explains how this process can lead to chronic noncommunicable diseases (4) affecting organs ...
Can Zeyneloglu+17 more
wiley +1 more source
A transcription factor for cold sensation!
The ability to feel hot and cold is critical for animals and human beings to survive in the natural environment. Unlike other sensations, the physiology of cold sensation is mostly unknown.
Milbrandt Jeffrey+3 more
doaj +1 more source
Transcription Factor-DNA Binding Via Machine Learning Ensembles [PDF]
We present ensemble methods in a machine learning (ML) framework combining predictions from five known motif/binding site exploration algorithms. For a given TF the ensemble starts with position weight matrices (PWM's) for the motif, collected from the ...
DeLisi, Charles, Fan, Yue, Kon, Mark
core
Hierarchy and Feedback in the Evolution of the E. coli Transcription Network [PDF]
The E.coli transcription network has an essentially feedforward structure, with, however, abundant feedback at the level of self-regulations. Here, we investigate how these properties emerged during evolution.
Atkinson+28 more
core +2 more sources
From omics to AI—mapping the pathogenic pathways in type 2 diabetes
Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan+2 more
wiley +1 more source
TRIM16 transcription factor in prostate cancer
The aim of this investigation was to reveal the expression TRIM16, ERα, ERβ and AR in prostate cancer tissues compared to benign hyperplasia and clinical and morphological parameters.Materials and methods.
L. V. Spirina+5 more
doaj +1 more source
JASPAR (http://jaspar.genereg.net) is an open-access database storing curated, non-redundant transcription factor (TF) binding profiles representing transcription factor binding preferences as position frequency matrices for multiple species in six ...
Anthony Mathelier+14 more
semanticscholar +1 more source
ERBIN limits epithelial cell plasticity via suppression of TGF‐β signaling
In breast and lung cancer patients, low ERBIN expression correlates with poor clinical outcomes. Here, we show that ERBIN inhibits TGF‐β‐induced epithelial‐to‐mesenchymal transition in NMuMG breast and A549 lung adenocarcinoma cell lines. ERBIN suppresses TGF‐β/SMAD signaling and reduces TGF‐β‐induced ERK phosphorylation.
Chao Li+3 more
wiley +1 more source