| Description |
1 online resource (xix, 372 pages) : illustrations |
| Contents |
Computational Intelligence: foundations, perspectives, and recent trends / Swagatam Das, Ajith Abraham, and B.K. Panigrahi -- Fundamentals of pattern analysis / Basabi Chakraborty -- Biological informatics: data, tools and applications / Kevin Byron, Miguel Cervantes-Cervantes and Jason T.L. Wang -- Sequence Analysis -- Promoter recognition using neural network approaches / T. Sobha Rani, S. Durga Bhavani and S. Bapi Raju -- Predicting microRNA prostate cancer target genes / Francesco Masulli, Stefano Rovetta and Giuseppe Russo -- Structural search in RNA motif databases / Dongrong Wen and Jason T.L. Wang -- Kernels on protein structures / Sourangshu Bhattacharya, Chiranjib Bhattacharyya and Nagasuma R. Chandra -- Characterization of conformational patterns in active and inactive forms of kinases using protein blocks approach / Garima Agarwal, Dhurvas Chandrasekaran Dinesh, Narayanaswamy Srinivasan, Alexandre G. de Brevern |
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Kernel applications in cheminformatics / Aaron Smalter and Jun Huan -- In-silico drug design using a computational intelligence technique / Soumi Sengupta and Sanghamitra Bandyopadhyay -- Integrated differential fuzzy clustering for analysis of microarray data / Indrajit Saha and Ujjwal Maulik -- Identifying potential gene markers using SVM classifier ensemble / Anirban Mukhopadhyay, Ujjwal Maulik and Sanghamitra Bandyopadhyay -- Gene microarray data analysis using parallel point symmetry-based clustering / Ujjwal Maulik and Anasua Sarker -- Techniques for prioritization of possible disease genes / Jieun Jeong and Jake Y. Chen -- Prediction of protein protein interactions / Angshuman Bagchi -- Analyzing topological properties of protein-protein interaction networks / Malay Bhattacharyya and Sanghamitra Bandyopadhyay |
| Summary |
"Computational Intelligence (CI) is a successor of artificial intelligence combining elements of learning, adaptation, evolution and logic to create programs that are, in some sense, intelligent. CI exhibits an ability to learn or deal with new situations, such that the system is perceived to possess one or more attributes of reason. The different methodologies in CI work synergistically and provide, in one form or another, flexible information processing capabilities for handling a huge volume of real life data with noises, ambiguity, and missing values. Solving problems often involves search for useful regularities or patterns in large amounts of data. A typical characteristic of biological data is high dimensionality with low sample size. This poses grand challenges to traditional pattern analysis techniques, necessitating the development of sophisticated approaches--Provided by publisher |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Bioinformatics.
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Computational biology.
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Artificial intelligence.
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Pattern recognition systems.
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Computational Biology
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Artificial Intelligence
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Gene Expression Profiling
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Pattern Recognition, Automated
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artificial intelligence.
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NATURE -- Reference.
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SCIENCE -- Life Sciences -- General.
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SCIENCE -- Life Sciences -- Biology.
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Artificial intelligence
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Bioinformatics
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Computational biology
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Pattern recognition systems
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Bio-informatica.
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Patroonherkenning.
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Genexpressie.
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Neurale netwerken.
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MicroRNA.
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Kristallografie.
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Eiwitten.
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Geneesmiddelen.
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Systeembiologie.
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| Form |
Electronic book
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| Author |
Maulik, Ujjwal.
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Bandyopadhyay, Sanghamitra, 1968-
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Wang, Jason T. L.
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| ISBN |
9780470872345 |
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0470872349 |
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9780470872352 |
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0470872357 |
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