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Data and Text Processing for Health and Life Sciences
This open access book is a step-by-step introduction on how shell scripting can help solve many of the data processing tasks that Health and Life specialists face everyday with minimal software dependencies. The examples presented in the book show how simple command line tools can be used and combined to retrieve data and text from web resources, to filter and mine literature, and to explore the semantics encoded in biomedical ontologies. To store data this book relies on open standard text file formats, such as TSV, CSV, XML, and OWL, that can be open by any text editor or spreadsheet application. The first two chapters, Introduction and Resources, provide a brief introduction to the shell ...
Data Management of Protein Interaction Networks
Current PPI databases do not offer sophisticated querying interfaces and especially do not integrate existing information about proteins. Current algorithms for PIN analysis use only topological information, while emerging approaches attempt to exploit the biological knowledge related to proteins and kinds of interaction, e.g. protein function, localization, structure, described in Gene Ontology or PDB. The book discusses technologies, standards and databases for, respectively, generating, representing and storing PPI data. It also describes main algorithms and tools for the analysis, comparison and knowledge extraction from PINs. Moreover, some case studies and applications of PINs are also discussed.
Introduction to Bio-Ontologies
Introduction to Bio-Ontologies explores the computational background of ontologies. Emphasizing computational and algorithmic issues surrounding bio-ontologies, this self-contained text helps readers understand ontological algorithms and their applications.The first part of the book defines ontology and bio-ontologies. It also explains the importan
Advanced Data Mining Technologies in Bioinformatics
"This book covers research topics of data mining on bioinformatics presenting the basics and problems of bioinformatics and applications of data mining technologies pertaining to the field"--Provided by publisher.
Perspective of DNA Computing in Computer Science
DNA or Deoxyribonucleic Acid computing is an emerging branch of computing that uses DNA sequence, biochemistry, and hardware for encoding genetic information in computers. Here, information is represented by using the four genetic alphabets or DNA bases, namely A (Adenine), G (Guanine), C (Cytosine), and T (Thymine), instead of the binary representation (1 and 0) used by traditional computers. This is achieved because short DNA molecules of any arbitrary sequence of A, G, C, and T can be synthesized to order. DNA computing is mainly popular for three reasons: (i) speed (ii) minimal storage requirements, and (iii) minimal power requirements. There are many applications of DNA computing in the...
The Semantic Web - ISWC 2013
The two-volume set LNCS 8218 and 8219 constitutes the refereed proceedings of the 12th International Semantic Web Conference, ISWC 2013, held in Sydney, Australia, in October 2013. The International Semantic Web Conference is the premier forum for Semantic Web research, where cutting edge scientific results and technological innovations are presented, where problems and solutions are discussed, and where the future of this vision is being developed. It brings together specialists in fields such as artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, human-computer interaction, natural language processing, and the social sciences. Part 1 (LNCS 8218) contains a total of 45 papers which were presented in the research track. They were carefully reviewed and selected from 210 submissions. Part 2 (LNCS 8219) contains 16 papers from the in-use track which were accepted from 90 submissions. In addition, it presents 10 contributions to the evaluations and experiments track and 5 papers of the doctoral consortium.
Formal Methods for Managing and Processing Ontology Alignments
Ontologies are formal knowledge representation methods that can provide means for a shared understanding of a given domain. To enable meaningful communication and interoperability between two or more information systems that utilize independently created ontologies, a bridge between them is necessary, often referred to as an ontology alignment. Formal Methods for Managing and Processing Ontology Alignments provides complete ontology alignment lifecycle, including modelling, methods, and maintenance processes. Summarizing the author's research from the past ten years, this book consolidates findings previously published in prestigious international journals and presented at leading conference...
Bio-Inspired Systems: Computational and Ambient Intelligence
This volume presents the set of final accepted papers for the tenth edition of the IWANN conference “International Work-Conference on Artificial neural Networks” held in Salamanca (Spain) during June 10–12, 2009. IWANN is a biennial conference focusing on the foundations, theory, models and applications of systems inspired by nature (mainly, neural networks, evolutionary and soft-computing systems). Since the first edition in Granada (LNCS 540, 1991), the conference has evolved and matured. The list of topics in the successive Call for - pers has also evolved, resulting in the following list for the present edition: 1. Mathematical and theoretical methods in computational intelligence....
Medical Informatics: Concepts, Methodologies, Tools, and Applications
Provides a collection of medical IT research in topics such as clinical knowledge management, medical informatics, mobile health and service delivery, and gene expression.
11th International Conference on Practical Applications of Computational Biology & Bioinformatics
Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next-generation sequencing technologies, together with novel and constantly evolving, distinct types of omics data technologies, have created an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intell...
