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Today, a single laboratory can generate a vast amount of biological data. There is a wealth of data already available in public databases, which makes the modern life sciences almost dependent on bioinformatics. This book brings together an international team of experts to discuss the state-of-the-art from several fields of bioinformatics, from the automatic identification and classification of viruses to the analysis of the transcriptome of single cells and plants, including artificial intelligence algorithms to discover biomarkers and text mining approaches to help in the interpretation of the findings. Machine learning, pattern discovery and analysis, error correction, Bayesian inference and novel computational techniques to discover chromosomal rearrangements continue to play crucial roles in biological discovery, and all of them are explored in chapters of this book. In sum, this book contains high-quality chapters that provide excellent views into key topics of current bioinformatics research, topics that should remain important for the next several years.

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