BERT4Bitter: a bidirectional encoder representations from transformers (BERT)-based model for improving the prediction of bitter peptides
Motivation The identification of bitter peptides through experimental approaches is an
expensive and time-consuming endeavor. Due to the huge number of newly available …
expensive and time-consuming endeavor. Due to the huge number of newly available …
StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides
P Charoenkwan, W Chiangjong… - Briefings in …, 2021 - academic.oup.com
The release of interleukin (IL)-6 is stimulated by antigenic peptides from pathogens as well
as by immune cells for activating aggressive inflammation. IL-6 inducing peptides are …
as by immune cells for activating aggressive inflammation. IL-6 inducing peptides are …
Deepm5C: a deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy
As one of the most prevalent post-transcriptional epigenetic modifications, N5-
methylcytosine (m5C) plays an essential role in various cellular processes and disease …
methylcytosine (m5C) plays an essential role in various cellular processes and disease …
Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework
Origins of replication sites (ORIs), which refers to the initiative locations of genomic DNA
replication, play essential roles in DNA replication process. Detection of ORIs' distribution in …
replication, play essential roles in DNA replication process. Detection of ORIs' distribution in …
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 …
STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction
Protein post-translational modification (PTM) is an important regulatory mechanism that
plays a key role in both normal and disease states. Acetylation on lysine residues is one of …
plays a key role in both normal and disease states. Acetylation on lysine residues is one of …
SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins
Thermophilic proteins (TPPs) are important in the field of protein biochemistry and
development of new enzymes. Thus, computational methods must be urgently developed to …
development of new enzymes. Thus, computational methods must be urgently developed to …
Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2
Abstract Coronavirus disease 2019 (COVID-19) has impacted public health as well as
societal and economic well-being. In the last two decades, various prediction algorithms and …
societal and economic well-being. In the last two decades, various prediction algorithms and …
THRONE: a new approach for accurate prediction of human RNA N7-methylguanosine sites
Abstract N 7-methylguanosine (m7G) is an essential, ubiquitous, and positively charged
modification at the 5′ cap of eukaryotic mRNA, modulating its export, translation, and …
modification at the 5′ cap of eukaryotic mRNA, modulating its export, translation, and …
UMPred-FRL: A new approach for accurate prediction of umami peptides using feature representation learning
Umami ingredients have been identified as important factors in food seasoning and
production. Traditional experimental methods for characterizing peptides exhibiting umami …
production. Traditional experimental methods for characterizing peptides exhibiting umami …