Machine intelligence in peptide therapeutics: A next‐generation tool for rapid disease screening
S Basith, B Manavalan, T Hwan Shin… - Medicinal research …, 2020 - Wiley Online Library
Discovery and development of biopeptides are time‐consuming, laborious, and dependent
on various factors. Data‐driven computational methods, especially machine learning (ML) …
on various factors. Data‐driven computational methods, especially machine learning (ML) …
Artificial intelligence: Machine learning approach for screening large database and drug discovery
PP Parvatikar, S Patil, K Khaparkhuntikar, S Patil… - Antiviral Research, 2023 - Elsevier
Recent research in drug discovery dealing with many faces difficulties, including
development of new drugs during disease outbreak and drug resistance due to rapidly …
development of new drugs during disease outbreak and drug resistance due to rapidly …
HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation
Motivation Therapeutic peptides failing at clinical trials could be attributed to their toxicity
profiles like hemolytic activity, which hamper further progress of peptides as drug …
profiles like hemolytic activity, which hamper further progress of peptides as drug …
Meta-4mCpred: a sequence-based meta-predictor for accurate DNA 4mC site prediction using effective feature representation
DNA N4-methylcytosine (4mC) is an important genetic modification and plays crucial roles in
differentiation between self and non-self DNA and in controlling DNA replication, cell cycle …
differentiation between self and non-self DNA and in controlling DNA replication, cell cycle …
mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation
Motivation Cardiovascular disease is the primary cause of death globally accounting for
approximately 17.7 million deaths per year. One of the stakes linked with cardiovascular …
approximately 17.7 million deaths per year. One of the stakes linked with cardiovascular …
iAFPs-EnC-GA: identifying antifungal peptides using sequential and evolutionary descriptors based multi-information fusion and ensemble learning approach
Fungal infections have become a serious health concern for human beings worldwide.
Fungal infections usually occur when the invading fungus appear on a particular part of the …
Fungal infections usually occur when the invading fungus appear on a particular part of the …
iUmami-SCM: a novel sequence-based predictor for prediction and analysis of umami peptides using a scoring card method with propensity scores of dipeptides
Umami or the taste of monosodium glutamate represents one of the major attractive taste
modalities in humans. Therefore, knowledge about biophysical and biochemical properties …
modalities in humans. Therefore, knowledge about biophysical and biochemical properties …
SDM6A: a web-based integrative machine-learning framework for predicting 6mA sites in the rice genome
DNA N 6-adenine methylation (6mA) is an epigenetic modification in prokaryotes and
eukaryotes. Identifying 6mA sites in rice genome is important in rice epigenetics and …
eukaryotes. Identifying 6mA sites in rice genome is important in rice epigenetics and …
iBCE-EL: a new ensemble learning framework for improved linear B-cell epitope prediction
Identification of B-cell epitopes (BCEs) is a fundamental step for epitope-based vaccine
development, antibody production, and disease prevention and diagnosis. Due to the …
development, antibody production, and disease prevention and diagnosis. Due to the …
MLCPP 2.0: an updated cell-penetrating peptides and their uptake efficiency predictor
B Manavalan, MC Patra - Journal of Molecular Biology, 2022 - Elsevier
Cell-penetrating peptides (CPPs) translocate into the cell as various biologically active
conjugates and possess numerous biomedical applications. Several machine learning …
conjugates and possess numerous biomedical applications. Several machine learning …