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Pattern Recognition in Bioinformatics
In the post-genomic era, a holistic understanding of biological systems and p- cesses,inalltheircomplexity,is criticalincomprehendingnature’schoreography of life. As a result, bioinformatics involving its two main disciplines, namely, the life sciences and the computational sciences, is fast becoming a very promising multidisciplinary research ?eld. With the ever-increasing application of lar- scalehigh-throughputtechnologies,suchasgeneorproteinmicroarraysandmass spectrometry methods, the enormous body of information is growing rapidly. Bioinformaticians are posed with a large number of di?cult problems to solve, arising not only due to the complexities in acquiring the molecular infor- ti...
Pattern Recognition in Bioinformatics
This book constitutes the refereed proceedings of the 7th International Conference on Pattern Recognition in Bioinformatics, PRIB 2012, held in Tokyo, Japan, in November 2012. The 24 revised full papers presented were carefully reviewed and selected from 33 submissions. Their topics are widely ranging from fundamental techniques, sequence analysis to biological network analysis. The papers are organized in topical sections on generic methods, visualization, image analysis, and platforms, applications of pattern recognition techniques, protein structure and docking, complex data analysis, and sequence analysis.
Pattern Recognition in Bioinformatics
This book constitutes the refereed proceedings of the 6th International Conference on Pattern Recognition in Bioinformatics, PRIB 2011, held in Delft, The Netherlands, in November 2011. The 29 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers cover the wide range of possible applications of bioinformatics in pattern recognition: novel algorithms to handle traditional pattern recognition problems such as (bi)clustering, classification and feature selection; applications of (novel) pattern recognition techniques to infer and analyze biological networks and studies on specific problems such as biological image analysis and the relation between sequence and structure. They are organized in the following topical sections: clustering, biomarker selection and classification, network inference and analysis, image analysis, and sequence, structure, and interactions.
Proceedings Of The 5th Asia-pacific Bioinformatics Conference
High-throughput sequencing and functional genomics technologies have given us the human genome sequence as well as those of other experimentally, medically, and agriculturally important species, and have enabled large-scale genotyping and gene expression profiling of human populations. Databases containing large numbers of sequences, polymorphisms, structures, and gene expression profiles of normal and diseased tissues are being rapidly generated for human and model organisms. Bioinformatics is thus rapidly growing in importance in the annotation of genomic sequences; the understanding of the interplay among and between genes and proteins; the analysis of genetic variability of species; the identification of pharmacological targets; and the inference of evolutionary origins, mechanisms, and relationships. This proceedings volume contains an up-to-date exchange of knowledge, ideas, and solutions to conceptual and practical issues of bioinformatics by researchers, professionals, and industrial practitioners at the 5th Asia-Pacific Bioinformatics Conference held in Hong Kong in January 2007./a
Pattern Recognition in Bioinformatics
This book constitutes the refereed proceedings of the 5th International Conference on Pattern Recognition in Bioinformatics, PRIB 2010, held in Nijmegen, The Netherlands, in September 2010. The 38 revised full papers presented were carefully reviewed and selected from 46 submissions. The field of bioinformatics has two main objectives: the creation and maintenance of biological databases and the analysis of life sciences data in order to unravel the mysteries of biological function. Computer science methods such as pattern recognition, machine learning, and data mining have a great deal to offer the field of bioinformatics.
Functionally Relevant Macromolecular Interactions of Disordered Proteins
Disordered proteins are relatively recent newcomers in protein science. They were first described in detail by Wright and Dyson, in their J. Mol. Biol. paper in 1999. First, it was generally thought for more than a decade that disordered proteins or disordered parts of proteins have different amino acid compositions than folded proteins, and various prediction methods were developed based on this principle. These methods were suitable for distinguishing between the disordered (unstructured) and structured proteins known at that time. In addition, they could predict the site where a folded protein binds to the disordered part of a protein, shaping the latter into a well-defined 3D structure. ...
Machine Learning in Bioinformatics
An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalizatio...
Neural Information Processing
The four-volume set CCIS 1791, 1792, 1793 and 1794 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022. The 213 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
