AIMC Topic: Proteins

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Plant Reactome and PubChem: The Plant Pathway and (Bio)Chemical Entity Knowledgebases.

Methods in molecular biology (Clifton, N.J.)
Plant Reactome (https://plantreactome.gramene.org) and PubChem ( https://pubchem.ncbi.nlm.nih.gov ) are two reference data portals and resources for curated plant pathways, small molecules, metabolites, gene products, and macromolecular interactions....

Using Gene Ontology to Annotate and Prioritize Microarray Data.

Methods in molecular biology (Clifton, N.J.)
The results of high-throughput experiments consist of numerous candidate genes, proteins, or other molecules potentially associated with diseases. A challenge for omics science is the knowledge extraction from the results and the filtering of promisi...

Session introduction: AI-driven Advances in Modeling of Protein Structure.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
The last few years mark dramatic improvements in modeling of protein structure. Progress was initially due to breakthroughs in residue-residue contact prediction, first with global statistical models and later with deep learning. These advancements w...

Artificial Intelligence-Enabled De Novo Design of Novel Compounds that Are Synthesizable.

Methods in molecular biology (Clifton, N.J.)
Development of computer-aided de novo design methods to discover novel compounds in a speedy manner to treat human diseases has been of interest to drug discovery scientists for the past three decades. In the beginning, the efforts were mostly concen...

Ultrahigh Throughput Protein-Ligand Docking with Deep Learning.

Methods in molecular biology (Clifton, N.J.)
Ultrahigh-throughput virtual screening (uHTVS) is an emerging field linking together classical docking techniques with high-throughput AI methods. We outline mechanistic docking models' goals and successes. We present different AI accelerated workflo...

DL-SMILES#: A Novel Encoding Scheme for Predicting Compound Protein Affinity Using Deep Learning.

Combinatorial chemistry & high throughput screening
INTRODUCTION: Drug repositioning aims to screen drugs and therapeutic goals from approved drugs and abandoned compounds that have been identified as safe. This trend is changing the landscape of drug development and creating a model of drug repositio...

Structure-aware protein-protein interaction site prediction using deep graph convolutional network.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interactions (PPI) play crucial roles in many biological processes, and identifying PPI sites is an important step for mechanistic understanding of diseases and design of novel drugs. Since experimental approaches for PPI ...

DeepSec: a deep learning framework for secreted protein discovery in human body fluids.

Bioinformatics (Oxford, England)
MOTIVATION: Human proteins that are secreted into different body fluids from various cells and tissues can be promising disease indicators. Modern proteomics research empowered by both qualitative and quantitative profiling techniques has made great ...