Computational Analysis of Proteomes and Genomes
A special issue of BioChem (ISSN 2673-6411).
Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 13045
2. CNC - Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504 Coimbra, Portugal
Interests: data science; drug discovery; deep learning; computational chemistry; structural biology; protein–protein complexes; modeling; GPCRs; functional selectivity
Special Issues, Collections and Topics in MDPI journals
The world is in urgent need of new cutting-edge computational tools that can create useful knowledge from information that is being published quickly and in a fragmented manner, delivering more tailored therapies against key multifactorial diseases. Despite the vast scientific and technological advances in drug research and development (R&D), as well as the amount of time and funding involved, we are witnessing a steady decline in pharmaceutical productivity in the last decades due to: i) lack of safety—high toxicity and many side effects are still significant reasons why a large percentage of drugs fail at pre-clinical and clinical stages; ii) patient-related constraints—human biological complexity and high genomic variability lead to different responses to therapy at both the individual and population level; iii) target-related issues—target identification and validation are the main reasons for project withdrawal in early stages, mainly due to the lack of understanding of the complexity and multifactorial character of infectious diseases. We need better-informed decisions in drug development, which means more robust and faster identification of the best targets and drug candidates to advance to preclinical and clinical trials. It is time to take advantage of the big boom of data availability, as well as the existence of powerful and cheaper software/hardware that allows the high performance of top in silico algorithms to enhance and accelerate scientific discoveries in this area.
As such, this Special Issue welcomes original research articles, short communications, and review papers. Potential topics include, but are not limited to, computational omics (proteomics, genomics, transcriptomics, metagenomics, and metabolomics) and their associated methodologies, data mining applied to different biological settings, phylogenetic and systematic analysis, network analysis, next-generation sequencing analysis, etc.
Dr. Irina S. Moreira
Manuscript Submission Information
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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. BioChem is an international peer-reviewed open access quarterly 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 1000 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.
- artificial intelligence
- big data
- network analysis
- phylogenetic analysis
- NGS analysis