Complexes of physically interacting proteins constitute fundamental functional units that drive almost all biological processes within cells. A faithful reconstruction of the entire set of protein complexes (the "complexosome") is therefore important not only to understand the composition of complexes but also the higher level functional organization within cells. Advances over the last several years, particularly through the use of high-throughput proteomics techniques, have made it possible to map substantial fractions of protein interactions (the "interactomes") from model organisms including Arabidopsis thaliana (a flowering plant), Caenorhabditis elegans (a nematode), Drosophila melanogaster (fruit fly), and Saccharomyces cerevisiae (budding yeast). These interaction datasets have enabled systematic inquiry into the identification and study of protein complexes from organisms. Computational methods have played a significant role in this context, by contributing accurate, efficient, and exhaustive ways to analyze the enormous amounts of data. These methods have helped to compensate for some of the limitations in experimental datasets including the presence of biological and technical noise and the relative paucity of credible interactions. In this book, we systematically walk through computational methods devised to date (approximately between 2000 and 2016) for identifying protein complexes from the network of protein interactions (the protein-protein interaction (PPI) network). We present a detailed taxonomy of these methods, and comprehensively evaluate them for protein complex identification across a variety of scenarios including the absence of many true interactions and the presence of false-positive interactions (noise) in PPI networks. Based on this evaluation, we highlight challenges faced by the methods, for instance in identifying sparse, sub-, or small complexes and in discerning overlapping complexes, and reveal how a combination of strategies is necessary to accurately reconstruct the entire complexosome.

This detailed volume provides a comprehensive collection of classic and cutting-edge methods and techniques in mapping protein-protein interactions. The chapters include a variety of in vitro and in vivo experimental methods covering cell biology, biochemistry, and biophysics. In addition, the book also explores in silico methods including sequence-, structure-, and phylogenetic profile-based approaches as well as gene expression and machine learning methods. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step and readily reproducible laboratory protocols, as well as tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Protein-Protein Interactions: Methods and Protocols serves as an ideal guide for researchers working in protein science and beyond.

This volume explores techniques that study interactions between proteins in different species, and combines them with context-specific data, analysis of omics datasets, and assembles individual interactions into higher-order semantic units, i.e., protein complexes and functional modules. The chapters in this book cover computational methods that solve diverse tasks such as the prediction of functional protein-protein interactions; the alignment-based comparison of interaction networks by SANA; using the RaptorX-ComplexContact webserver to predict inter-protein residue-residue contacts; the docking of alternative confirmations of proteins participating in binary interactions and the visually-guided selection of a docking model using COZOID; the detection of novel functional units by KeyPathwayMiner and how PathClass can use such de novo pathways to classify breast cancer subtypes. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary hardware- and software, step-by-step, readily reproducible computational protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and comprehensive, Protein-Protein Interaction Networks: Methods and Protocols is a valuable resource for both novice and expert researchers who are interested in learning more about this evolving field.

Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. With contributions from leading experts, Network Medicine introduces this rapidly evolving field of research, which promises to revolutionize the diagnosis and treatment of human diseases.

Microbiota are a promising and fascinating subject in biology because they integrate the microbial communities in humans, animals, plants, and the environment. In humans, microbiota are associated with the gut, skin, and genital, oral, and respiratory organs. The plant microbial community is referred to as "holobiont," and it is influential in the maintenance and health of plants, which themselves play a role in animal health and the environment. The contents of Microbiome-Host Interactions cover all areas as well as new research trends in the fields of plant, animal, human, and environmental microbiome interactions. The book covers microbiota in polar soil environments, in health and disease, in Caenorhabditis elegans, and in agroecosystems, as well as in rice root and actinorhizal root nodules, speleothems, and marine shallow-water hydrothermal vents. Moreover, this book provides comprehensive accounts of advanced next-generation DNA sequencing, metagenomic techniques, high-throughput 16S rRNA sequencing, and understanding nucleic acid sequence data from fungal, algal, viral, bacterial, cyanobacterial, actinobacterial, and archaeal communities using QIIME software (Quantitative Insights into Microbial Ecology). FEATURES Summarizes recent insight in microbiota and host interactions in distinct habitats, including Antarctic, hydrothermal vents, speleothems, oral, skin, gut, feces, reproductive tract, soil, root, root nodules, forests, and mangroves Illustrates the high-throughput amplicon sequencing, computational techniques involved in the microbiota analysis, downstream analysis and visualization, and multivariate analysis commonly used for microbiome analysis Describes probiotics and prebiotics in the composition of the gut microbiota, skin microbiome impact in dermatologic disease prevention, and microbial communities in the reproductive tract of humans and animals Presents information in a reachable way for students, teachers, researchers, microbiologists, computational biologists, and other professionals who are interested in strengthening or enlarging their knowledge about microbiome analysis with next-generation DNA sequencing in the different branches of the sciences