IEEE/ACM transactions on computational biology and bioinformatics
Mar 7, 2019
Antimicrobial peptides are short amino acid sequences that may be antibacterial, antifungal, and antiviral. Most machine learning methodologies applied to identifying antibacterial peptides have developed feature vectors of identical lengths for each...
BACKGROUND: Ligand-binding proteins play key roles in many biological processes. Identification of protein-ligand binding residues is important in understanding the biological functions of proteins. Existing computational methods can be roughly categ...
International journal of molecular sciences
Feb 23, 2019
The interactions between ncRNAs and proteins are critical for regulating various cellular processes in organisms, such as gene expression regulations. However, due to limitations, including financial and material consumptions in recent experimental m...
Viruses are worldwide pathogens with a high impact on the human population. Despite the constant efforts to fight viral infections, there is a need to discover and design new drug candidates. Antiviral peptides are molecules with confirmed activity a...
The prediction of peptide-protein or protein-protein interactions (PPI) is a challenging task, especially if amino acid sequences are the only information available. Machine learning methods allow us to exploit the information content in PPI datasets...
In this study, the binding of allergens to antibody-receptor complexes was investigated. This process is important in understanding the allergic response. A BioNetGen model that simulates this process, combined with a novel method for encoding steric...
PPAR-δ agonists are known to enhance fatty acid metabolism, preserving glucose and physical endurance and are suggested as candidates for treating metabolic diseases. None have reached the clinic yet. Our Machine Learning algorithm called "Iterative ...
IEEE/ACM transactions on computational biology and bioinformatics
Jan 18, 2019
Accurately identifying DNA-binding proteins (DBPs) from protein sequence information is an important but challenging task for protein function annotations. In this paper, we establish a novel computational method, named TargetDBP, for accurately targ...
Rapid, accurate prediction of protein structure from amino acid sequence would accelerate fields as diverse as drug discovery, synthetic biology and disease diagnosis. Massively improved prediction of protein structures has been driven by improving t...
BACKGROUND: To further our understanding of immunopeptidomics, improved tools are needed to identify peptides presented by major histocompatibility complex class I (MHC-I). Many existing tools are limited by their reliance upon chemical affinity data...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.