Recent Advances in Computational Biology and Bioinformatics

Dear Colleagues,

Computational biology and bioinformatics are rapidly evolving interdisciplinary field that develops and applied numerous new algorithms to analyze large multi-omics data. In the era of big data, the transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. With the advancement of this field, researchers were able to develop numerous methods for analytical methods, mathematical modeling and simulation.

Interestingly, the researchers developed numerous algorithms to analyze DNA, RNA and protein sequence analysis, phylogenetics, protein folding, and technological platforms.

Bioinformatics and computational biology have many applications, and one of the most common is the identification of protein 3D structure, molecular modeling, and folding to predict the possible function or model the behavior of molecules, and other molecular structures. It would help in the development of biomedical drugs for various complicated human diseases. Apart from this, computational biology and bioinformatics progression are also related to biological networks and the system biology area, where large-scale biological networks, such as the biome, interactome, and microbiome, have been created. Apparently, the most interesting new field of bioinformatics, text mining, has tremendous research potential. This encourages to query, mine, and examine clinical text that would be useful for biological scientists and/or clinicians.

Although, with the advancement of sequencing technologies, the booming of multimodal sequencing data creates a valuable resource for us to understand cellular heterogeneity and molecular the mechanism at a comprehensive level. However, data storage and the complexity of interpreting enormous amounts of data obtained with next-generation sequencing (NGS) still remain a computational challenge to researchers. To provide a useful and comprehensive perspective of sequencing data many algorithms are present and researchers keep on developing new methods and technologies. The applications of NGS in clinical oncology have already proven their importance in mortality reduction via complete genomic profile screening.

To analyze any large volumes of biological data the primary force behind the current and future advancement is the development of new computational biology technologies, including networking, visualization, graphics, and molecular modeling.

In order to acknowledge the progress of this field, we are inviting manuscripts related to the recent advances in computational biology and bioinformatics.

The Special Issue will cover but not be limited to the following research topics:

1. Development of novel bioinformatics and computational algorithm, model, and tools including statistical methods.
2. Development of database.
3. Application of machine learning, deep learning, and artificial intelligence using biological data such as proteomics, transcriptomics, and epigenetics.
4. Resources for advancement of the field.
5. Review articles summarizing the progress of bioinformatics and computational biology research.

Dr. Ravindra Kumar
Dr. Anjali Garg
Dr. Bandana Kumari
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. Axioms 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 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.

• bioinformatics
• computational biology
• machine learning
• deep learning
• artificial intelligence
• proteomics
• transcriptomics
• epigenetics
• cancer biology
• high-throughput data analysis