AIMC Topic: Computational Biology

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Integrative multi-omics identifies S100A8/IGFBP5/CTSK/S100P as dual diagnostic biomarkers and therapeutic targets in Crohn's disease: from computational discovery to preclinical validation.

International immunopharmacology
Crohn's disease (CD) is a chronic inflammatory bowel condition that significantly impairs patients' quality of life. With no cure currently available, the need to discover novel biomarkers and develop effective therapeutic strategies is paramount. Th...

Curcumenol exerts anti-pulmonary fibrosis effects through modulation of the immune signature target SPP1: based on comprehensive bioinformatics and experiments validation.

International immunopharmacology
BACKGROUND: The efficacy of Curcuma wenyujin (C. wenyujin) volatile oil components in the treatment of lung diseases, including pulmonary fibrosis (PF), is gradually being recognized. However, the anti-PF potential and underlying mechanisms of curcum...

Multiview Deep Learning Framework for Precise Prediction of Transcription Factor Binding Sites.

Journal of chemical information and modeling
Transcription factors (TFs) are essential proteins that regulate gene expression by specifically binding to transcription factor binding sites (TFBSs) within DNA sequences. Their ability to precisely control the transcription process is crucial for u...

Potentials and limitations in the application of Convolutional Neural Networks for mosquito species identification using wing images.

PLoS computational biology
This study addresses the pressing global health burden of mosquito-borne diseases by investigating the application of Convolutional Neural Networks (CNNs) for mosquito species identification using wing images. Conventional identification methods are ...

ProteinWeaver: A webtool to visualize ontology-annotated protein networks.

PloS one
Molecular interaction networks are a vital tool for studying biological systems. While many tools exist that visualize a protein or a pathway within a network, no tool provides the ability for a researcher to consider a protein's position in a networ...

A Machine Learning Model for the Proteome-Wide Prediction of Lipid-Interacting Proteins.

Journal of chemical information and modeling
Lipids are essential metabolites that play critical roles in multiple cellular pathways. Like many primary metabolites, mutations that disrupt lipid synthesis can be lethal. Proteins involved in lipid synthesis, trafficking, and modification, are tar...

Sarah Teichmann: Science always wins if we work together.

The Journal of experimental medicine
Sarah Teichmann is a professor at the University of Cambridge, where she leads a research group that uses a combination of genomics, artificial intelligence (AI), and bioinformatics to further understand various aspects of immunity. She is also one o...

UCP2 is identified as a therapeutic target for abdominal aortic aneurysm by comprehensive bioinformatic analysis and experimental validation.

Biochemical and biophysical research communications
Abdominal aortic aneurysm (AAA) is a potentially life-threatening vascular condition that currently lacks effective pharmacological treatment. The disease is strongly associated with chronic inflammation, where immune cells like macrophages play a cr...

Diagnostic PANoptosis-related genes in acute kidney injury: bioinformatics, machine learning, and validation.

Annals of medicine
BACKGROUND: Acute kidney injury (AKI) is a prevalent and life-threatening condition characterized by abrupt renal function decline and subsequent inflammatory cascades. PANoptosis has emerged as a significant contributor to the pathophysiology of AKI...

RENOVO-NF1 accurately predicts NF1 missense variant pathogenicity.

Human genomics
Identification of a pathogenic variant in NF1 is diagnostic for neurofibromatosis, but is often impossible at the moment of variant detection due to many factors including allelic heterogeneity, sequence homology, and the lack of functional assays. C...