A comprehensive comparative review of sequence-based predictors of DNA-and RNA-binding residues
J Yan, S Friedrich, L Kurgan - Briefings in bioinformatics, 2016 - academic.oup.com
Motivated by the pressing need to characterize protein–DNA and protein–RNA interactions
on large scale, we review a comprehensive set of 30 computational methods for high …
on large scale, we review a comprehensive set of 30 computational methods for high …
Computational tools to study RNA-protein complexes
S Bheemireddy, S Sandhya, N Srinivasan… - Frontiers in molecular …, 2022 - frontiersin.org
RNA is the key player in many cellular processes such as signal transduction, replication,
transport, cell division, transcription, and translation. These diverse functions are …
transport, cell division, transcription, and translation. These diverse functions are …
Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning
Abstract DNA N4-methylcytosine (4mC) modification represents a novel epigenetic
regulation. It involves in various cellular processes, including DNA replication, cell cycle and …
regulation. It involves in various cellular processes, including DNA replication, cell cycle and …
[HTML][HTML] In-Silico analysis reveals lower transcription efficiency of C241T variant of SARS-CoV-2 with host replication factors MADP1 and hnRNP-1
A Chaudhari, M Chaudhari, S Mahera, Z Saiyed… - Informatics in Medicine …, 2021 - Elsevier
Novel severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has claimed more
than 3.3 million lives worldwide and still counting. As per the GISAID database, the …
than 3.3 million lives worldwide and still counting. As per the GISAID database, the …
A boosting approach for prediction of protein-RNA binding residues
Background RNA binding proteins play important roles in post-transcriptional RNA
processing and transcriptional regulation. Distinguishing the RNA-binding residues in …
processing and transcriptional regulation. Distinguishing the RNA-binding residues in …
DFpin: Deep learning–based protein-binding site prediction with feature-based non-redundancy from RNA level
X Zhao, Y Zhang, X Du - Computers in biology and medicine, 2022 - Elsevier
Highlights•This paper identifies the protein interaction nucleotide sites with the
characteristics of the RNA sequence.•This paper removes redundant data based on the …
characteristics of the RNA sequence.•This paper removes redundant data based on the …
Comprehensive survey and comparative assessment of RNA-binding residue predictions with analysis by RNA type
With close to 30 sequence-based predictors of RNA-binding residues (RBRs), this
comparative survey aims to help with understanding and selection of the appropriate tools …
comparative survey aims to help with understanding and selection of the appropriate tools …
Genome-wide functional annotation of human protein-coding splice variants using multiple instance learning
The vast majority of human multiexon genes undergo alternative splicing and produce a
variety of splice variant transcripts and proteins, which can perform different functions. These …
variety of splice variant transcripts and proteins, which can perform different functions. These …
RPI-Bind: a structure-based method for accurate identification of RNA-protein binding sites
RNA and protein interactions play crucial roles in multiple biological processes, while these
interactions are significantly influenced by the structures and sequences of protein and RNA …
interactions are significantly influenced by the structures and sequences of protein and RNA …
Efficient mapping of RNA‐binding residues in RNA‐binding proteins using local sequence features of binding site residues in protein‐RNA complexes
Protein‐RNA interactions play vital roles in plethora of biological processes such as
regulation of gene expression, protein synthesis, mRNA processing and biogenesis …
regulation of gene expression, protein synthesis, mRNA processing and biogenesis …