AIMC Topic: Protein Interaction Maps

Clear Filters Showing 281 to 290 of 453 articles

Protein complex identification based on weighted PPI network with multi-source information.

Journal of theoretical biology
Proteins form complexes to accomplish biological functions such as transcription of DNA, translation of mRNA and cell growth. Detection of protein complexes from protein-protein interaction (PPI) networks is the first step for the analysis of biologi...

A novel matrix of sequence descriptors for predicting protein-protein interactions from amino acid sequences.

PloS one
Protein-protein interactions (PPIs) play an important role in the life activities of organisms. With the availability of large amounts of protein sequence data, PPIs prediction methods have attracted increasing attention. A variety of protein sequenc...

Deep Learning to Therapeutically Target Unreported Complexes.

Trends in pharmacological sciences
The disruption of large protein-protein (PP) interfaces remains a challenge in targeted therapy. Designing drugs that compete with binding partners is daunting, especially when the structure of the protein complex is unknown. To address the problem w...

SLMF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization.

IEEE/ACM transactions on computational biology and bioinformatics
Synthetic lethality (SL) is a promising concept for novel discovery of anti-cancer drug targets. However, wet-lab experiments for detecting SLs are faced with various challenges, such as high cost, low consistency across platforms, or cell lines. The...

Deep Learning and Random Forest Approach for Finding the Optimal Traditional Chinese Medicine Formula for Treatment of Alzheimer's Disease.

Journal of chemical information and modeling
It has demonstrated that glycogen synthase kinase 3β (GSK3β) is related to Alzheimer's disease (AD). On the basis of the world largest traditional Chinese medicine (TCM) database, a network-pharmacology-based approach was utilized to investigate TCM ...

Analysis of differentially expressed genes in rheumatoid arthritis and osteoarthritis by integrated microarray analysis.

Journal of cellular biochemistry
BACKGROUND: Rheumatoid arthritis (RA) and osteoarthritis (OA) were two major types of joint diseases. This study aimed to explore the mechanism underlying OA and RA and analyze their difference by integrated analysis of multiple gene expression data ...

Exploring semi-supervised variational autoencoders for biomedical relation extraction.

Methods (San Diego, Calif.)
The biomedical literature provides a rich source of knowledge such as protein-protein interactions (PPIs), drug-drug interactions (DDIs) and chemical-protein interactions (CPIs). Biomedical relation extraction aims to automatically extract biomedical...

Mechanism of glucocerebrosidase activation and dysfunction in Gaucher disease unraveled by molecular dynamics and deep learning.

Proceedings of the National Academy of Sciences of the United States of America
The lysosomal enzyme glucocerebrosidase-1 (GCase) catalyzes the cleavage of a major glycolipid glucosylceramide into glucose and ceramide. The absence of fully functional GCase leads to the accumulation of its lipid substrates in lysosomes, causing G...

Gene ontology improves template selection in comparative protein docking.

Proteins
Structural characterization of protein-protein interactions is essential for our ability to study life processes at the molecular level. Computational modeling of protein complexes (protein docking) is important as the source of their structure and a...

Identifying mouse developmental essential genes using machine learning.

Disease models & mechanisms
The genes that are required for organismal survival are annotated as 'essential genes'. Identifying all the essential genes of an animal species can reveal critical functions that are needed during the development of the organism. To inform studies o...