New Advances in Bioinformatics and Mathematical Modelling
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematical Biology".
Deadline for manuscript submissions: 28 February 2025 | Viewed by 840
Special Issue Editors
Interests: biophysics and biomedical engineering
Interests: mathematical modelling; metaheuristic algorithms; process control; generalised nets; intuitionistic fuzzy sets; intercriteria analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
“New Advances in Bioinformatics and Mathematical Modelling” is a Special Issue of the peer-reviewed open access journal Mathematics, which aims to publish original articles of a high scientific standard in all computational and applied mathematics areas.
The topic Bioinformatics can be defined as the application of computational techniques to understand and organize information related to biological objects. Bioinformatics is an interdisciplinary field that requires the collaboration of scientists in biology, chemistry, informatics, medicine, mathematics, engineering, and healthcare to achieve applied and scientific breakthroughs in understanding biological processes by developing and applying efficient computational and statistical approaches.
This Special Issue aims to disseminate scientific achievements and innovations in Bioinformatics, including:
- Genomic bioinformatics:
- Identification of candidate genes and single nucleotide polymorphisms;
- Processing of large arrays of images and signals in order to sequence and annotate genomes and their observed mutations;
- Processing of large arrays of images and signals to analyze the expression and regulation of genes and proteins;
- Comparing, analyzing, and interpreting genetic and genomic data;
- Simulation and modeling of DNA, RNA, proteins, and biomolecular interactions;
- Predicting functions of genes and proteins.
- Computational biology:
- Development of new mathematical formulas and statistical measures for evaluating relationships in large data sets;
- Modeling of biological systems and functions;
- Generation of models based on accumulated data from experiments;
- Analyzing and interpreting biological data;
- In silico analyses and experiments;
- Modeling chemical reactions in the cell.
Dr. Lyudmila Todorova
Prof. Dr. Olympia Roeva
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. Mathematics 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 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
- bioinformatics (genome or protein) databases
- molecular cell biology, cell simulation, and modeling
- experimental design
- clustering, classification, and association rules
- interactive data exploration and discovery
- search-based data analytics
- big data analytics
- machine learning
- hidden Markov models
- global optimization
- dynamic programming
- evolutionary computation
- meta-heuristics algorithms
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