The field of proteomics has developed rapidly over the past decade nurturing the need for a detailed introduction to the various informatics topics that underpin the main liquid chromatography tandem mass spectrometry (LC-MS/MS) protocols used for protein identification and quantitation. Proteins are a key component of any biological system, and monitoring proteins using LC-MS/MS proteomics is becoming commonplace in a wide range of biological research areas. However, many researchers treat proteomics software tools as a black box, drawing conclusions from the output of such tools without considering the nuances and limitations of the algorithms on which such software is based. This book seeks to address this situation by bringing together world experts to provide clear explanations of the key algorithms, workflows and analysis frameworks, so that users of proteomics data can be confident that they are using appropriate tools in suitable ways.

Bringing together world experts to provide clear explanations of the key algorithms, workflows and analysis frameworks, Proteome Informatics will provide a detailed introduction to the main informatics topics that underpin the various LC-MS/MS protocols used for protein identification and quantitation.

Protein informatics is a newer name for an already existing discipline. It encompasses the techniques used in bioinformatics and molecular modeling that are related to proteins. While bioinformatics is mainly concerned with the collection, organization, and analysis of biological data, molecular modeling is devoted to representation and manipulation of the structure of proteins. Protein informatics requires substantial prerequisites on computer science, mathematics, and molecular biology. The approach chosen here, allows a direct and rapid grasp on the subject starting from basic knowledge of algorithm design, calculus, linear algebra, and probability theory. An Introduction to Protein Informatics, a professional monograph will provide the reader a comprehensive introduction to the field of protein informatics. The text emphasizes mathematical and computational methods to tackle the central problems of alignment, phylogenetic reconstruction, and prediction and sampling of protein structure. An Introduction to Protein Informatics is designed for a professional audience, composed of researchers and practitioners within bioinformatics, molecular modeling, algorithm design, optimization, and pattern recognition. This book is also suitable as a graduate-level text for students in computer science, mathematics, and biomedicine.

Proteomics is a multifaceted, interdisciplinary field which studies the complexity and dynamics of proteins in biological systems. It combines powerful separation and analytical technology with advanced informatics to understand the function of proteins in the cell and in the body. This book provides a clear conceptual description of each facet of proteomics, describes recent advances in technology and thinking in each area, and provides details of how these have been applied to a variety of biological problems. It is written by expert practitioners in the field, from industry, research institutions, and the clinic. It provides junior and experienced researchers with an invaluable proteomic reference, and gives fascinating glimpses of the future of this dynamic field.

The handling and analysis of data generated by proteomics investigations represent a challenge for computer scientists, biostatisticians, and biologists to develop tools for storing, retrieving, visualizing, and analyzing genomic data. Informatics in Proteomics examines the ongoing advances in the application of bioinformatics to proteomics researc

The authors aim to shed light on the practicality of using machine learning in finding complex chemoinformatics and bioinformatics applications as well as identifiying AI in biological and chemical data points. The chapters are designed in such a way that they highlight the important role of AI in chemistry and bioinformatics particularly for the classification of diseases, selection of features and compounds, dimensionality reduction and more. In addition, they assist in the organization and optimal use of data points generated from experiments performed using AI techniques. This volume discusses the development of automated tools and techniques to aid in research plans. Features Covers AI applications in bioinformatics and chemoinformatics Demystifies the involvement of AI in generating biological and chemical data Provides an Introduction to basic and advanced chemoinformatics computational tools Presents a chemical biology based toolset for artificial intelligence usage in drug design Discusses computational methods in cancer, genome mapping, and stem cell research

This book provides an integrated treatment of the structure and function of nucleic acids, proteins, and glycans, including thorough coverage of relevant computational biochemistry. The text begins with an introduction to the biomacromolecules, followed by discussion of methods of isolation and purification, physiochemical and biochemical properties, and structural characteristics. The next section of the book deals with sequence analysis, analysis of conformation using spectroscopy, chemical synthesis, and computational approaches. The following chapters discuss biomolecular interactions, enzyme action, gene transmission, signal transduction, and biomacromolecular informatics. The author concludes with presenting the latest findings in genomics, proteomics, glycomics, and biomacromolecular evolution. This text is an invaluable resource for research professionals wishing to move into genomics, proteomics, and glycomics research. It is also useful for students in biochemistry, molecular biology, bioengineering, biotechnology, and bioinformatics.