Biological sequence classification: A review on data and general methods
C Ao, S Jiao, Y Wang, L Yu, Q Zou - Research, 2022 - spj.science.org
With the rapid development of biotechnology, the number of biological sequences has
grown exponentially. The continuous expansion of biological sequence data promotes the …
grown exponentially. The continuous expansion of biological sequence data promotes the …
Progresses in predicting post-translational modification
KC Chou - International Journal of Peptide Research and …, 2020 - Springer
Identification of the sites of post-translational modifications (PTMs) in protein, RNA, and DNA
sequences is currently a very hot topic. This is because the information thus obtained is very …
sequences is currently a very hot topic. This is because the information thus obtained is very …
Attention-based multi-label neural networks for integrated prediction and interpretation of twelve widely occurring RNA modifications
Recent studies suggest that epi-transcriptome regulation via post-transcriptional RNA
modifications is vital for all RNA types. Precise identification of RNA modification sites is …
modifications is vital for all RNA types. Precise identification of RNA modification sites is …
DeePromoter: robust promoter predictor using deep learning
The promoter region is located near the transcription start sites and regulates transcription
initiation of the gene by controlling the binding of RNA polymerase. Thus, promoter region …
initiation of the gene by controlling the binding of RNA polymerase. Thus, promoter region …
H2Opred: a robust and efficient hybrid deep learning model for predicting 2'-O-methylation sites in human RNA
O-methylation (2OM) is the most common post-transcriptional modification of RNA. It plays a
crucial role in RNA splicing, RNA stability and innate immunity. Despite advances in high …
crucial role in RNA splicing, RNA stability and innate immunity. Despite advances in high …
iHBP-DeepPSSM: Identifying hormone binding proteins using PsePSSM based evolutionary features and deep learning approach
Hormone binding proteins (HBPs) are soluble carrier proteins that can non-covalently and
selectively interact with the human hormone. HBPs plays a significant role in human life, but …
selectively interact with the human hormone. HBPs plays a significant role in human life, but …
NmRF: identification of multispecies RNA 2'-O-methylation modification sites from RNA sequences
C Ao, Q Zou, L Yu - Briefings in bioinformatics, 2022 - academic.oup.com
O-methylation (Nm) is a post-transcriptional modification of RNA that is catalyzed by 2'-O-
methyltransferase and involves replacing the H on the 2′-hydroxyl group with a methyl …
methyltransferase and involves replacing the H on the 2′-hydroxyl group with a methyl …
iN6-Methyl (5-step): Identifying RNA N6-methyladenosine sites using deep learning mode via Chou's 5-step rules and Chou's general PseKNC
Abstract N6-methyladenosine (m 6 A) is an RNA methylation modification and it is involved
in various biological progresses such as translation, alternative splicing, degradation …
in various biological progresses such as translation, alternative splicing, degradation …
MsDBP: exploring DNA-binding proteins by integrating multiscale sequence information via Chou's five-step rule
DNA-binding proteins are crucial to alternative splicing, methylation, and the structural
composition of the DNA. The existing experimental methods for identifying DNA-binding …
composition of the DNA. The existing experimental methods for identifying DNA-binding …
iDNA6mA (5-step rule): Identification of DNA N6-methyladenine sites in the rice genome by intelligent computational model via Chou's 5-step rule
DNA methylation is an elementary epigenetic process. The N6-methyladenine is related to a
large kind of biological processes ie, transcription, DNA replication, and repair. In genome …
large kind of biological processes ie, transcription, DNA replication, and repair. In genome …