Anti-cancer peptides: status and future prospects
The dramatic rise in cancer incidence, alongside treatment deficiencies, has elevated
cancer to the second-leading cause of death globally. The increasing morbidity and mortality …
cancer to the second-leading cause of death globally. The increasing morbidity and mortality …
Large-scale comparative assessment of computational predictors for lysine post-translational modification sites
Lysine post-translational modifications (PTMs) play a crucial role in regulating diverse
functions and biological processes of proteins. However, because of the large volumes of …
functions and biological processes of proteins. However, because of the large volumes of …
iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences
Structural and physiochemical descriptors extracted from sequence data have been widely
used to represent sequences and predict structural, functional, expression and interaction …
used to represent sequences and predict structural, functional, expression and interaction …
iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization
Sequence-based analysis and prediction are fundamental bioinformatic tasks that facilitate
understanding of the sequence (-structure)-function paradigm for DNAs, RNAs and proteins …
understanding of the sequence (-structure)-function paradigm for DNAs, RNAs and proteins …
iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data
With the explosive growth of biological sequences generated in the post-genomic era, one
of the most challenging problems in bioinformatics and computational biology is to …
of the most challenging problems in bioinformatics and computational biology is to …
AMYPred-FRL is a novel approach for accurate prediction of amyloid proteins by using feature representation learning
Amyloid proteins have the ability to form insoluble fibril aggregates that have important
pathogenic effects in many tissues. Such amyloidoses are prominently associated with …
pathogenic effects in many tissues. Such amyloidoses are prominently associated with …
ACPred-Fuse: fusing multi-view information improves the prediction of anticancer peptides
B Rao, C Zhou, G Zhang, R Su… - Briefings in bioinformatics, 2020 - academic.oup.com
Fast and accurate identification of the peptides with anticancer activity potential from large-
scale proteins is currently a challenging task. In this study, we propose a new machine …
scale proteins is currently a challenging task. In this study, we propose a new machine …
xDeep-AcPEP: deep learning method for anticancer peptide activity prediction based on convolutional neural network and multitask learning
J Chen, HH Cheong, SWI Siu - Journal of chemical information …, 2021 - ACS Publications
Cancer is one of the leading causes of death worldwide. Conventional cancer treatment
relies on radiotherapy and chemotherapy, but both methods bring severe side effects to …
relies on radiotherapy and chemotherapy, but both methods bring severe side effects to …
Post-translational modification prediction via prompt-based fine-tuning of a GPT-2 model
Post-translational modifications (PTMs) are pivotal in modulating protein functions and
influencing cellular processes like signaling, localization, and degradation. The complexity …
influencing cellular processes like signaling, localization, and degradation. The complexity …
Machine learning approaches and their current application in plant molecular biology: A systematic review
Abstract Machine learning (ML) is a field of artificial intelligence that has rapidly emerged in
molecular biology, thus allowing the exploitation of Big Data concepts in plant genomics. In …
molecular biology, thus allowing the exploitation of Big Data concepts in plant genomics. In …