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Special Issues
Development, Application, and Analysis of Bioinformatics Tools
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Development, Application, and Analysis of Bioinformatics Tools

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Technologies and Resources for Genetics".

Deadline for manuscript submissions: closed (20 January 2024) | Viewed by 3129

Special Issue Editors

Dr. Hui Yu

E-Mail Website
Guest Editor
Comprehensive Cancer Center, Department of Internal Medicine, University of New Mexico, Albuquerque, NM 87109, USA
Interests: bioinformatics; computational biology; system biology; genomic analysis; integrative bioinformatics; network bioinformatics
Dr. Jing Yang

E-Mail Website
Guest Editor
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
Interests: bioinformatics; computational biology; system biology; genomic analysis; integrative bioinformatics; network bioinformatics

Special Issue Information

Dear Colleagues,

Propelled by microarrays, high-throughput sequencing, and other ever-advancing technologies, biology and translational medicine have become data-rich sciences, which therefore hinge on powerful big data analysis tools tailored to specific biomedical domain problems. To date, many ingenious software tools, such as Samtools, edgeR, and PLINK, have contributed massively to recent biomedical research progress. Research on bioinformatics and its applications increases exponentially with every passing year, allowing millions of data related to genetics, epigenomics, transcriptomics, proteomics, metabolomics, and other biological moieties across thousands of tissues and organisms to be compiled, cleaned, stored, and integrated for the purpose of systematic studies. For example, due to the continuous progress in high-throughput sequencing technologies, it has become more crucial than ever to develop new approaches and novel applications for bulk and single-cell sequencing data.  

We envision that new bioinformatics tools should assume a leading role in creating new opportunities for advancing biomedical discoveries. Herein, we call for all kinds of bioinformatics woks that combine computer programing, information engineering, mathematics, and statistics to handle biomedical problems and/or pursue biomedical insights. We encourage the submission of original research and reviews that focus on the full spectrum of bioinformatics to the analysis of biological and biomedical data such as, but not limited to, the following:

  • Novel methods and tools to interpret biological data;
  • The use of suitable approaches to unveil new biological insights;
  • Databases curating and visualizing biomedical data;
  • Novel applications for multi-omics integration.

Dr. Hui Yu
Dr. Jing Yang
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.

Keywords

  • RNA-seq, DNA-seq
  • genomics, transcriptomics, proteomics, and metabolomics
  • data mining
  • functional genomics
  • machine learning
  • database

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Published Papers (2 papers)

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9 pages, 1814 KiB  
Article
Constructing an Interactive and Integrated Analysis and Identification Platform for Pathogenic Microorganisms to Support Surveillance Capacity
by Yang Song, Songchao Zhong, Yixiao Li, Mengnan Jiang and Qiang Wei
Genes 2023, 14(12), 2156; https://doi.org/10.3390/genes14122156 - 29 Nov 2023
Viewed by 1015
Abstract
Introduction: Whole genome sequencing (WGS) holds significant promise for epidemiological inquiries, as it enables the identification and tracking of pathogenic origins and dissemination through comprehensive genome analysis. This method is widely preferred for investigating outbreaks and monitoring pathogen activity. However, the effective utilization [...] Read more.
Introduction: Whole genome sequencing (WGS) holds significant promise for epidemiological inquiries, as it enables the identification and tracking of pathogenic origins and dissemination through comprehensive genome analysis. This method is widely preferred for investigating outbreaks and monitoring pathogen activity. However, the effective utilization of microbiome sequencing data remains a challenge for clinical and public health experts. Through the National Pathogen Resource Center, we have constructed a dynamic and interactive online analysis platform to facilitate the in-depth analysis and use of pathogen genomic data, by public health and associated professionals, to support infectious disease surveillance framework building and capacity warnings. Method: The platform was implemented using the Java programming language, and the front-end pages were developed using the VUE framework, following the MVC (Model–View–Controller) pattern to enable interactive service functionalities for front-end data collection and back-end data computation. Cloud computing services were employed to integrate biological information analysis tools for conducting fundamental analysis on sequencing data. Result: The platform achieved the goal of non-programming analysis, providing an interactive visual interface that allows users to visually obtain results by setting parameters in web pages. Moreover, the platform allows users to export results in various formats to further support their research. Discussion: We have established a dynamic and interactive online platform for bioinformatics analysis. By encapsulating the complex background experiments and analysis processes in a cloud-based service platform, the complex background experiments and analysis processes are presented to the end-user in a simple and interactive manner. It facilitates real-time data mining and analysis by allowing users to independently select parameters and generate analysis results at the click of a button, based on their needs, without the need for a programming foundation. Full article
(This article belongs to the Special Issue Development, Application, and Analysis of Bioinformatics Tools)
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18 pages, 18552 KiB  
Article
Haplotype-Resolution Transcriptome Analysis Reveals Important Responsive Gene Modules and Allele-Specific Expression Contributions under Continuous Salt and Drought in Camellia sinensis
by Qing Zhang, Ziqi Ye, Yinghao Wang, Xingtan Zhang and Weilong Kong
Genes 2023, 14(7), 1417; https://doi.org/10.3390/genes14071417 - 8 Jul 2023
Cited by 1 | Viewed by 1627
Abstract
The tea plant, Camellia sinensis (L.) O. Kuntze, is one of the most important beverage crops with significant economic and cultural value. Global climate change and population growth have led to increased salt and drought stress, negatively affecting tea yield and quality. The [...] Read more.
The tea plant, Camellia sinensis (L.) O. Kuntze, is one of the most important beverage crops with significant economic and cultural value. Global climate change and population growth have led to increased salt and drought stress, negatively affecting tea yield and quality. The response mechanism of tea plants to these stresses remains poorly understood due to the lack of reference genome-based transcriptional descriptions. This study presents a high-quality genome-based transcriptome dynamic analysis of C. sinensis’ response to salt and drought stress. A total of 2244 upregulated and 2164 downregulated genes were identified under salt and drought stress compared to the control sample. Most of the differentially expression genes (DEGs) were found to involve divergent regulation processes at different time points under stress. Some shared up- and downregulated DEGs related to secondary metabolic and photosynthetic processes, respectively. Weighted gene co-expression network analysis (WGCNA) revealed six co-expression modules significantly positively correlated with C. sinensis’ response to salt or drought stress. The MEpurple module indicated crosstalk between the two stresses related to ubiquitination and the phenylpropanoid metabolic regulation process. We identified 1969 salt-responsive and 1887 drought-responsive allele-specific expression (ASE) genes in C. sinensis. Further comparison between these ASE genes and tea plant heterosis-related genes suggests that heterosis likely contributes to the adversity and stress resistance of C. sinensis. This work offers new insight into the underlying mechanisms of C. sinensis’ response to salt and drought stress and supports the improved breeding of tea plants with enhanced salt and drought tolerance. Full article
(This article belongs to the Special Issue Development, Application, and Analysis of Bioinformatics Tools)
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