Recent Advances in Bioinformatics: Novel Techniques, Methods, and Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: 20 July 2024 | Viewed by 2878

Special Issue Editors

School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
Interests: bioinformatics; computational peptides; drug design
Special Issues, Collections and Topics in MDPI journals
Department of Chemistry, New York University, New York, NY 10003, USA
Interests: development of computational protocols for structure-based inhibitor design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce the forthcoming Special Issue, "Recent Advances in Bioinformatics: Novel Techniques, Methods, and Applications," which aims to showcase the latest research and developments in the field of bioinformatics. This Special Issue will offer a platform for researchers, scholars, and practitioners to present their innovative work, discuss novel methodologies, and share cutting-edge applications in bioinformatics.

The rapid growth in biological data generation has presented unprecedented opportunities for researchers to gain insights into complex biological systems. Bioinformatics has become a critical discipline for the analysis, interpretation, and prediction of this vast amount of data, enabling for the discovery of new biological knowledge and the development of novel therapeutic strategies.

This Special Issue invites original research articles, review articles, and short communications that focus on recent advancements in bioinformatics, including, but not limited to:

  • Novel computational algorithms and methods for biological data analysis;
  • Machine learning and artificial intelligence approaches in bioinformatics;
  • Next-generation sequencing data analysis and genome assembly;
  • Genomic variation detection, characterization, and functional analysis;
  • Gene expression and regulation analysis;
  • Protein structure prediction and functional annotation;
  • Integrative multi-omics analysis;
  • Systems biology and network analysis;
  • Metagenomics and microbiome data analysis;
  • Drug discovery and personalized medicine;
  • Computational tools and databases for bioinformatics research;
  • Emerging applications and challenges in bioinformatics.

We encourage submissions from interdisciplinary teams that combine expertise in biology, computer science, statistics, and engineering to address complex biological questions. This Special Issue aims to provide a comprehensive overview of the current state of the art in bioinformatics and inspire future research directions in this exciting field.

Dr. Peng Zhou
Dr. Chao 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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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

  • bioinformatics
  • computational biology
  • machine learning
  • artificial intelligence
  • next-generation sequencing
  • genomic variation
  • gene expression
  • protein structure
  • multi-omics analysis
  • drug discovery
  • personalized medicine
  • bioinformatics tools
  • databases

Published Papers (3 papers)

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Research

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11 pages, 3256 KiB  
Article
FungiRegEx: A Tool for Pattern Identification in Fungal Proteomic Sequences Using Regular Expressions
by Victor Terrón-Macias, Jezreel Mejia, Miguel Angel Canseco-Pérez, Mirna Muñoz and Miguel Terrón-Hernández
Appl. Sci. 2024, 14(11), 4429; https://doi.org/10.3390/app14114429 - 23 May 2024
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Abstract
In the context of proteomic-scale research, it is imperative to automatically analyze numerous species and subspecies to discern distinctive characteristics present in multiple species of the fungi kingdom that contain sequences of interest that could fulfill a specific biological function. To achieve this, [...] Read more.
In the context of proteomic-scale research, it is imperative to automatically analyze numerous species and subspecies to discern distinctive characteristics present in multiple species of the fungi kingdom that contain sequences of interest that could fulfill a specific biological function. To achieve this, complex sequences must be recognized within an organism’s entire set of proteomes. Our study presents FungiRegEx, a piece of software that facilitates the identification of regular expressions of proteomes of fungal organisms and uses real-time data retrieval of the different species from the JGI Mycocosm database without the need to download any file. Integrating a graphical user interface that makes it easy to use, the tool offers regular expression searches on 2402 fungal species from the JGI Mycocosm portal. The tool was validated with the AXSXG sequence and the RXRL effector, demonstrating the effectiveness of FungiRegEx in identifying user-defined patterns in the recovered sequences. This tool allows customization and filtering, and it can save results if required, combining speed, adaptability, and ease of use. It provides an experience without a console and programming, displaying the results in a GUI and making them easier to read. Its architecture guarantees optimized use of resources, time consumption, and implementation flexibility, allowing the customization of specific software parameters for resource management. The tool’s potential for future research and exploration is emphasized, providing a nuanced perspective on its practical use within the fungal genomics community. The tools are available at the addresses mentioned in the text. Full article
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14 pages, 4132 KiB  
Article
Sulforaphane Target Protein Prediction: A Bioinformatics Analysis
by Francisco Alejandro Lagunas-Rangel
Appl. Sci. 2024, 14(3), 1052; https://doi.org/10.3390/app14031052 - 26 Jan 2024
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Abstract
Sulforaphane, a phytochemical found in cruciferous vegetables and various nutraceutical foods, plays a crucial role in promoting well-being and combating various diseases. Its remarkable effects are due to its intricate interactions with a wide range of proteins, some of which remain unidentified. In [...] Read more.
Sulforaphane, a phytochemical found in cruciferous vegetables and various nutraceutical foods, plays a crucial role in promoting well-being and combating various diseases. Its remarkable effects are due to its intricate interactions with a wide range of proteins, some of which remain unidentified. In this study, taking advantage of bioinformatics tools for protein target prediction, we identified 11 proteins as potential targets of sulforaphane. Due to its biological relevance and their correlation with transcriptomic changes observed in sulforaphane-treated cells, the possible interaction between sulforaphane and nicotinamide phosphoribosyltransferase (NAMPT) was further investigated. A docking analysis suggested that sulforaphane is strategically positioned at the entrance of the channel through which substrates enter, thus bypassing the active site of the enzyme. By forming hydrogen bonds with residues K189, R349, and S275, sulforaphane establishes a linkage with NAMPT. Dynamic molecular analyses further corroborated these observations, illustrating that these bonds allow sulforaphane to associate with NAMPT, mimicking the behavior of a NAMPT activator (NAT), a known activating compound of this enzyme. This collective evidence suggests that sulforaphane may activate NAMPT, providing valuable insights into a possible mechanism underlying its diverse biological effects. Full article
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Review

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26 pages, 2793 KiB  
Review
Bioinspired Algorithms for Multiple Sequence Alignment: A Systematic Review and Roadmap
by Mohammed K. Ibrahim, Umi Kalsom Yusof, Taiseer Abdalla Elfadil Eisa and Maged Nasser
Appl. Sci. 2024, 14(6), 2433; https://doi.org/10.3390/app14062433 - 13 Mar 2024
Viewed by 1272
Abstract
Multiple Sequence Alignment (MSA) plays a pivotal role in bioinformatics, facilitating various critical biological analyses, including the prediction of unknown protein structures and functions. While numerous methods are available for MSA, bioinspired algorithms stand out for their efficiency. Despite the growing research interest [...] Read more.
Multiple Sequence Alignment (MSA) plays a pivotal role in bioinformatics, facilitating various critical biological analyses, including the prediction of unknown protein structures and functions. While numerous methods are available for MSA, bioinspired algorithms stand out for their efficiency. Despite the growing research interest in addressing the MSA challenge, only a handful of comprehensive reviews have been undertaken in this domain. To bridge this gap, this study conducts a thorough analysis of bioinspired-based methods for MSA through a systematic literature review (SLR). By focusing on publications from 2010 to 2024, we aim to offer the most current insights into this field. Through rigorous eligibility criteria and quality standards, we identified 45 relevant papers for review. Our analysis predominantly concentrates on bioinspired-based techniques within the context of MSA. Notably, our findings highlight Genetic Algorithm and Memetic Optimization as the most commonly utilized algorithms for MSA. Furthermore, benchmark datasets such as BAliBASE and SABmark are frequently employed in evaluating MSA solutions. Structural-based methods emerge as the preferred approach for assessing MSA solutions, as revealed by our systematic literature review. Additionally, this study explores current trends, challenges, and unresolved issues in the realm of bioinspired algorithms for MSA, offering practitioners and researchers valuable insights and comprehensive understanding of the field. Full article
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