Encyclopedia of Bioinformatics and Computational Biology

Bioinformatics and Computational Biology (BCB) combine elements of computer science, information technology, mathematics, statistics, and biotechnology, providing the methodology and in silico solutions to mine biological data and processes, for knowledge discovery. In the era of molecular diagnostics, targeted drug design, translational medicine and Big Data for personalized medicine, computational methods for data analysis are essential tools for biochemistry, biology, biotechnology, pharmacology, biomedical and computer science, as well as mathematics and statistics. New areas are emerging, and relatively isolated fields are becoming current hot research areas in BCB, such as Artificial Intelligence, Quantitative Biology, Computational Vaccinology, Epidemiology and Infection Diffusion, Synthetic Biology, and Phenomics. The role of BCB in characterizing SARS-CoV-2 variants and facing the COVID-19 pandemic is just one example of how these tools can help us better prepare for such future events. This Encyclopedia comprises three sections, covering Methods, Topics, and Applications. The methodologies and algorithms underpinning BCB are described in the Methods section; Topics covers traditional areas such as phylogeny, as well as more recent areas such as translational bioinformatics, cheminformatics and environmental informatics; Applications provides guidance for commonly asked “how to” questions. Navigating the maze of confusing jargon and the plethora of software tools is often confronting for students and researchers alike. This comprehensive and unique resource provides up-to-date theory and application content to address molecular data analysis requirements, with precise definitions of terminology and lucid explanations by field experts.

Table of Contents:
I. Methods Algorithms Biological data models Computational models and languages for bioinformatics Artificial Intelligence and Machine Learning Deep Learning Data Mining Biological Networks Biostatistics Integrative Bioinformatics Ontology Pathways Text Mining Natural Language Processing Epidemiology and Pandemic surveillance Bioimage Analytics II. Topics Cheminformatics Disease Informatics Environmental (Biome) Informatics Functional Genomics Genome Informatics Immunoinformatics and Vaccinology Molecular Phylogeny Proteome Informatics Structural Bioinformatics Systems and Synthetic Biology Translational Bioinformatics Bioimage Informatics Interactomics Epidemiology III. Applications Biome mapping and ecological modelling Database Searching Drug Design Sequence Analysis Structure Analysis Genome Analysis Genome-Wise Association Studies (GWAS) Epigenomic Analysis Transcriptome Analysis Proteome Analysis Interactome Analysis Phylogenetic Analysis Vaccine Design Epitope Analysis Bioinformatics pipelines and workflows Metabolomics analysis Biomolecular engineering Biomarker discovery Network analysis

About the Author :
Shoba Ranganathan is an Honorary Professor of Bioinformatics in Applied Biosciences, Macquarie University. She was the first Chair of Bioinformatics in Australia (2004-22). She has held research and academic positions in India, USA, Singapore and Australia as well as a consultancy in industry. Shoba's research addresses several key areas of bioinformatics to understand biological systems using computational approaches. Her group has achieved both experience and expertise in different aspects of computational biology, ranging from metabolites and small molecules to biochemical networks, pathway analysis and computational systems biology. She has authored as well as edited several books and contributed several articles to the 1st edition of this Encyclopedia. She was awarded the 2023 Outstanding Contributions to the International Society for Computational Biology (ISCB) Award. She is an Honorary Senior Fellow of the Australian Society for Bioinformatics and Computational Biology since 2018 and an ISCB Fellow since 2023. Mario Cannataro is a Full Professor of Computer Engineering and Bioinformatics at University “Magna Graecia” of Catanzaro, Italy. He is the director of the Data Analytics research center and the chair of the Bioinformatics Laboratory. His current research interests include bioinformatics, medical informatics, artificial intelligence, sentiment analysis, data analytics, parallel and distributed computing. He is a member of the editorial boards of Briefings in Bioinformatics and IEEE/ACM Transactions on Computational Biology and Bioinformatics. He was guest editor of several special issues on bioinformatics and health informatics and organized several bioinformatics workshops in conjunction with ACM-BCB and IEEE-BIBM conferences. He has published three books and more than 300 papers in international journals and conference proceedings. Prof. Cannataro is a member of the Ethical Committee of the Calabria Region and a senior member of ACM, IEEE and SIBIM, He is currently a member of the steering committee of the Italian Bioinformatics Society (BITS) and of the Italian Association for Telemedicine and Medical Informatics (AITIM). Mohammad Asif Khan is a Professor and Associate Dean at the University of Doha for Science and Technology, Qatar. He earned his PhD from the National University of Singapore before joining Johns Hopkins University (JHU), USA, as a faculty member. He later became part of a pioneering JHU team to establish a collaboration with Perdana University (PU) in Malaysia, where he served as the Founding Dean of the School of Data Sciences and Founding Director of the Centre for Bioinformatics. Dr. Khan was also a visiting Professor at Bezmialem Vakif University, Istanbul, through Turkey’s “International Fellowship for Outstanding Researchers.” He is currently the President of the Asia-Pacific Bioinformatics Network and chairs the executive board of the Global Organisation for Bioinformatics Learning, Education, and Training. His research focuses on biological data warehousing and bioinformatics applications in virus study, immune responses, vaccines, drug design, and disease biomarkers.