An innovative title that provides a systematic overview of new alignment-free methods in genomics and bioinformatics, emphasizing their potential to add predictive capabilities to address major and ongoing questions in biological science.
Predictive Methods for Genomics and Evolution provides a coherent overview of the major alignment-based and alignment-free methods in genomics and bioinformatics, primarily based on DNA/RNA. Throughout the book, contrasts between current conventional methods and new alignment-free methods are presented and evaluated across a wide range of topics.
Written by a team of experienced academics with significant research experience in the field, Predictive Methods for Genomics and Evolution discusses key topics including:
Major unsolved problems in biology including the most fundamental concept of species, the nature of evolution and speciation, phylogenetic inference, pathogenesis, and the origin of life
Novel interpretations of current hypotheses from a biological perspective with broad applications in bioinformatics and medicine
Insights on the shift in the research landscape towards a broader application of more efficient alignment-free methods, enhanced by increased data availability, deeper knowledge of DNA/RNA structure, and powerful methods from the fields of machine learning and data science.
“Predictive Methods for Genomics and Evolution” is an essential guide in this field for professionals, academics, researchers, and students in the fields of genomics, evolutionary biology, phylogenetics and taxonomy, and computational biology and bioinformatics, as well as practitioners in related fields.
