Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.1
3.5
Journals
Genes
Special Issues
Proteins and Genes Bioinformatics: Analysis, Algorithms and Applications
share announcement

Proteins and Genes Bioinformatics: Analysis, Algorithms and Applications

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Bioinformatics".

Deadline for manuscript submissions: closed (25 April 2023) | Viewed by 3932

Special Issue Editors

Prof. Dr. M. Michael Gromiha

E-Mail Website
Guest Editor
Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India
Interests: bioinformatics; genome-wide analysis; protein-nucleic acid interactions; protein-protein interactions; protein structure and function; protein folding and stability; amino acid mutations; machine learning; NGS
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Y-h. Taguchi

E-Mail Website
Guest Editor
Department of Physics, Chuo University, Tokyo 112-8551, Japan
Interests: bioinformatics; tensor decomposition; feature selection
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The advanced developments in Biotechnology provide a wealth of data on genomes, proteomes, metabolomes and transcriptomes. This has been evidenced with the growth of data in gene expression profiles, amino acid sequences, protein three-dimensional structures and protein-protein interaction networks. The availability of data pave way to several analyses in biological and medical research, such as high-throughput protein structure prediction, genome-wide protein-protein interaction prediction, binding sites and interface structures in protein complexes, identification of post-transcription modification sites, single nucleotide polymorphism (SNP) prediction, gene expression profile data analysis and so on. The comprehensive analysis, development of efficient algorithms, software and tools for data integration and visualization are necessary in these cutting-edge research fields. 

This special issue provides a forum for researchers to present and discuss their latest research results to timely identify and address related problems and challenges, as well as compilation of data from the literature. We invite the submission of original research articles and/or reviews in this area.

Computational methods for protein and gene bioinformatics include but are not limited to:

  • protein structure analysis, folding and stability
  • secondary and tertiary structure prediction of globular and membrane proteins
  • analysis and prediction of protein-protein, protein-nucleic acid and protein-ligand interactions including contact sites, hotspots and interface
  • modeling and Analysis on protein interaction network
  • gene regulatory network modeling
  • disease related single nucleotide polymorphism identification
  • disease related cell signaling pathway identification
  • gene expression profile data analysis
  • Next Generation Sequence (NGS) analysis
  • deep learning.

Prof. Dr. M. Michael Gromiha
Prof. Dr. Y-h. Taguchi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

20 pages, 3653 KiB  
Article
Integrative Meta-Analysis of Huntington’s Disease Transcriptome Landscape
by Nela Pragathi Sneha, S. Akila Parvathy Dharshini, Y.-H. Taguchi and M. Michael Gromiha
Genes 2022, 13(12), 2385; https://doi.org/10.3390/genes13122385 - 16 Dec 2022
Cited by 2 | Viewed by 1862
Abstract
Huntington’s disease (HD) is a neurodegenerative disorder with autosomal dominant inheritance caused by glutamine expansion in the Huntingtin gene (HTT). Striatal projection neurons (SPNs) in HD are more vulnerable to cell death. The executive striatal population is directly connected with the Brodmann Area [...] Read more.
Huntington’s disease (HD) is a neurodegenerative disorder with autosomal dominant inheritance caused by glutamine expansion in the Huntingtin gene (HTT). Striatal projection neurons (SPNs) in HD are more vulnerable to cell death. The executive striatal population is directly connected with the Brodmann Area (BA9), which is mainly involved in motor functions. Analyzing the disease samples from BA9 from the SRA database provides insights related to neuron degeneration, which helps to identify a promising therapeutic strategy. Most gene expression studies examine the changes in expression and associated biological functions. In this study, we elucidate the relationship between variants and their effect on gene/downstream transcript expression. We computed gene and transcript abundance and identified variants from RNA-seq data using various pipelines. We predicted the effect of genome-wide association studies (GWAS)/novel variants on regulatory functions. We found that many variants affect the histone acetylation pattern in HD, thereby perturbing the transcription factor networks. Interestingly, some variants affect miRNA binding as well as their downstream gene expression. Tissue-specific network analysis showed that mitochondrial, neuroinflammation, vasculature, and angiogenesis-related genes are disrupted in HD. From this integrative omics analysis, we propose that abnormal neuroinflammation acts as a two-edged sword that indirectly affects the vasculature and associated energy metabolism. Rehabilitation of blood-brain barrier functionality and energy metabolism may secure the neuron from cell death. Full article
(This article belongs to the Special Issue Proteins and Genes Bioinformatics: Analysis, Algorithms and Applications)
►▼ Show Figures

Figure 1

16 pages, 4320 KiB  
Article
Bioinformatics Analysis of WRKY Family Genes in Erianthus fulvus Ness
by Haowen Chen, Xuzhen Li, Fusheng Li, Dengyu Li, Yang Dong and Yuanhong Fan
Genes 2022, 13(11), 2102; https://doi.org/10.3390/genes13112102 - 12 Nov 2022
Cited by 2 | Viewed by 1417
Abstract
One of the most prominent transcription factors in higher plants, the WRKY gene family, is crucial for secondary metabolism, phytohormone signaling, plant defense responses, and plant responses to abiotic stresses. It can control the expression of a wide range of target genes by [...] Read more.
One of the most prominent transcription factors in higher plants, the WRKY gene family, is crucial for secondary metabolism, phytohormone signaling, plant defense responses, and plant responses to abiotic stresses. It can control the expression of a wide range of target genes by coordinating with other DNA-binding or non-DNA-binding interacting proteins. In this study, we performed a genome-wide analysis of the EfWRKY genes and initially identified 89 members of the EfWRKY transcription factor family. Using some members of the OsWRKY transcription factor family, an evolutionary tree was built using the neighbor-joining (NJ) method to classify the 89 members of the EfWRKY transcription factor family into three major taxa and one unclassified group. Molecular weights ranged from 22,614.82 to 303,622.06 Da; hydrophilicity ranged from (−0.983)–(0.159); instability coefficients ranged from 40.97–81.30; lipid coefficients ranged from 38.54–91.89; amino acid numbers ranged from 213–2738 bp; isoelectric points ranged from 4.85–10.06. A signal peptide was present in EfWRKY41 but not in the other proteins, and EfWRK85 was subcellularly localized to the cell membrane. Chromosome localization revealed that the WRKY gene was present on each chromosome, proving that the conserved pattern WRKYGQK is the family’s central conserved motif. Conserved motif analysis showed that practically all members have this motif. Analysis of the cis-acting elements indicated that, in addition to the fundamental TATA-box, CAAT-box, and light-responsive features (GT1-box), there are response elements implicated in numerous hormones, growth regulation, secondary metabolism, and abiotic stressors. These results inform further studies on the function of EfWRKY genes and will lead to the improvement of sugarcane. Full article
(This article belongs to the Special Issue Proteins and Genes Bioinformatics: Analysis, Algorithms and Applications)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop