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Biomolecules
Special Issues
Bioinformatics and Mutations: New Techniques and Applications
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Bioinformatics and Mutations: New Techniques and Applications

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Bioinformatics and Systems Biology".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 2388

Special Issue Editor

Prof. Dr. Rosario M. Piro

E-Mail Website
Guest Editor
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
Interests: bioinformatics; computational biology

Special Issue Information

Dear Colleagues,

The efficient identification and analysis of both somatic and germline mutations remains an important research topic in computational biology. New sequencing techniques pose new problems, and the improvement or optimization of computational tools for existing techniques helps to increase the reliability of bioinformatics methods for clinical applications and personalized medicine. In addition, the intelligent use of existing tools can lead to important novel insights.

The goal of this Special Issue is to provide a platform for new techniques and methods as well as new applications of computational approaches to the identification and study of mutations, including structural variants.

The topic of this Special Issue is deliberately broad, including but not limited to:

  • Mutational processes, mutational patterns and mutational signatures;
  • Single-nucleotide variants, indels and structural variants;
  • Germline mutations in hereditary disorders and somatic mutations in cancer;
  • Evolutionary studies;
  • Metagenomics;
  • Novel methods and the use of existing approaches to provide novel insights.

We welcome papers that describe your latest developments and new findings, or review articles that portray the state of the art from a new perspective.

Prof. Dr. Rosario M. Piro
Guest Editor

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. Biomolecules 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 2700 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

  • cancer genomics
  • somatic mutations
  • mutation patterns
  • mutational signatures
  • mutational processes
  • computational oncology

Published Papers (1 paper)

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Research

18 pages, 2259 KiB  
Article
MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model
by Vasiliki Karalidou, Despoina Kalfakakou, Athanasios Papathanasiou, Florentia Fostira and George K. Matsopoulos
Biomolecules 2022, 12(11), 1552; https://doi.org/10.3390/biom12111552 - 24 Oct 2022
Cited by 3 | Viewed by 1781
Abstract
Implementation of next-generation sequencing (NGS) for the genetic analysis of hereditary diseases has resulted in a vast number of genetic variants identified daily, leading to inadequate variant interpretation and, consequently, a lack of useful clinical information for treatment decisions. Herein, we present MARGINAL [...] Read more.
Implementation of next-generation sequencing (NGS) for the genetic analysis of hereditary diseases has resulted in a vast number of genetic variants identified daily, leading to inadequate variant interpretation and, consequently, a lack of useful clinical information for treatment decisions. Herein, we present MARGINAL 1.0.0, a machine learning (ML)-based software for the interpretation of rare BRCA1 and BRCA2 germline variants. MARGINAL software classifies variants into three categories, namely, (likely) pathogenic, of uncertain significance and (likely) benign, implementing the criteria established by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG-AMP). We first annotated BRCA1 and BRCA2 variants using various sources. Then, we automatically implemented the ACMG-AMP criteria, and we finally constructed the ML model for variant classification. To maximize accuracy, we compared the performance of eight different ML algorithms in a classification scheme based on a serial combination of two classifiers. The model showed high predictive abilities with maximum accuracy of 92% and 98%, recall of 92% and 98% and specificity of 90% and 98% for the first and second classifiers, respectively. Our results indicate that using a gene and disease-specific ML automated software for clinical variant evaluation can minimize conflicting interpretations. Full article
(This article belongs to the Special Issue Bioinformatics and Mutations: New Techniques and Applications)
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