Knighting in sequence biology Edward N. Trifonov Genome classification, construction of phylogenetic trees, became today a major approach in studying evolutionary relatedness of various species in their vast - versity. Although the modern genome clustering delivers the trees which are very similar to those generated by classical means, and basic terminology is the same, the phenotypic traits and habitats are not anymore the playground for the classi- cation. The sequence space is the playground now. The phenotypic traits are - placed by sequence characteristics, “words”, in particular. Matter-of-factually, the phenotype and genotype merged, to confusion of both classical and modern p- logeneticists. Accordingly, a completely new vocabulary of stringology, information theory and applied mathematics took over. And a new brand of scientists emerged – those who do know the math and, simultaneously, (do?) know biology. The book is written by the authors of this new brand. There is no way to test their literacy in biology, as no biologist by training would even try to enter into the elite circle of those who masters their almost occult language. But the army of - formaticians, formal linguists, mathematicians humbly (or aggressively) longing to join modern biology, got an excellent introduction to the field of genome cl- tering, written by the team of their kin.

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

The book Gene Duplication consists of 21 chapters divided in 3 parts: General Aspects, A Look at Some Gene Families and Examining Bundles of Genes. The importance of the study of Gene Duplication stems from the realization that the dynamic process of duplication is the "sine qua non" underlying the evolution of all living matter. Genes may be altered before or after the duplication process thereby undergoing neofunctionalization, thus creating in time new organisms which populate the Earth.

Partitioning around medoids (Program PAM). Clustering large applications (Program CLARA). Fuzzy analysis (Program FANNY). Agglomerative Nesting (Program AGNES). Divisive analysis (Program DIANA). Monothetic analysis (Program MONA). Appendix.

This volume guides researchers on how to characterize, image rare, and hitherto unknown taxa and their interactions, to identify new functions and biomolecules and to understand how environmental changes condition the activity and the response of the organisms living with us and in our environment. Chapters cover different organism types (i.e., archaea, bacteria, fungi, protest, microfauna and microeukaryotes) and propose detailed protocols to produce high quality DNA, to analyse active microbial communities directly involved in complex interactions or processes through stable isotope probing, to identify and characterize of new functional genes, to image in situ interactions and to apply bioinformatics analysis tools to complex metagenomic or RNAseq sequence data. Written in the successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Microbial Environmental Genomics (MEG): Methods and Protocols, Second Edition aims to serve as a primary research reference for researchers in microbiology working to in the expanding field of molecular ecology and environmental genomics.

Genetic engineering and biotechnology along with conventional breeding have played an important role in developing superior cultivars by transferring economically important traits from distant, wild and even unrelated species to the cultivated varieties which otherwise could not have been possible with conventional breeding. There is a vast amount of literature pertaining to the genetic improvement of crops over last few decades. However, the wonderful results achieved by crop scientists in food legumes’ research and development over the years are scattered in different journals of the World. The two volumes in the series ‘Alien Gene Transfer in Crop Plants’ address this issue and offer a comprehensive reference on the developments made in major food crops of the world. These volumes aim at bringing the contributions from globally renowned scientists at one platform in a reader-friendly manner. The 1st volume entitled, ‘Alien Gene Transfer in Crop Plants: Innovations, Methods and Risk Assessment” will deal exclusively with the process and methodology. The contents of this volume have been designed to appraise the readers with all the theoretical and practical aspects of wide hybridization and gene transfer like processes and methods of gene transfer, role of biotechnology with special reference to embryo rescue, genetic transformation, protoplast fusion and molecular marker technology, problems such as cross incompatibility and barriers to distant hybridization and solutions to overcome them. Since wild and weedy relatives of crop plants may have negative traits associated with them, there are always possibilities of linkage drag while transferring alien alleles. Therefore, problems and limitations of alien gene transfer from these species will also be discussed in this series. Further, the associated risks with this and assessment of risks will also be given due weightage.

The genetic information being unlocked by advances in genomic and high throughput technologies is rapidly revolutionizing our understanding of developmental processes in bovine species. This information is allowing researchers unprecedented insight into the genetic basis of key traits. Bovine Genomics is the first book to bring together and synthesize the information learned through the bovine genome sequencing project and look at its practical application to cattle and dairy production. Bovine Genomics opens with foundational chapters on the domestication of cattle and traditional Mendelian genetics. Building on these chapters, coverage rapidly moves to quantitative genetics and the advances of whole genome technologies. Significant coverage is given to such topics as epigenetics, mapping quantitative trail loci, genome-wide association studies and genomic selection in cattle breeding. The book is a valuable synthesis of the field written by a global team of leading researchers. Providing wide-ranging coverage of the topic, Bovine Genomic, is an essential guide to the field. The basic and applied science will be of use to researchers, breeders, and advanced students.