Molecular biology is undergoing exponential growth in both the volume and complexity of biological data. This book offers the first comprehensive overview of data mining, preprocessing, postprocessing, and storage for biological data.

PREFACE xiii CONTRIBUTORS xv SECTION I BIOLOGICAL DATA PREPROCESSING PART A: BIOLOGICAL DATA MANAGEMENT 1 GENOME AND TRANSCRIPTOME SEQUENCE DATABASES FOR DISCOVERY, STORAGE, AND REPRESENTATION OF ALTERNATIVE SPLICING EVENTS 5 Bahar Taneri and Terry Gaasterland 2 CLEANING, INTEGRATING, AND WAREHOUSING GENOMIC DATA FROM BIOMEDICAL RESOURCES 35 Fouzia Moussouni and Laure Berti-Equille 3 CLEANSING OF MASS SPECTROMETRY DATA FOR PROTEIN IDENTIFICATION AND QUANTIFICATION 59 Penghao Wang and Albert Y. Zomaya 4 FILTERING PROTEIN–PROTEIN INTERACTIONS BY INTEGRATION OF ONTOLOGY DATA 77 Young-Rae Cho PART B: BIOLOGICAL DATA MODELING 5 COMPLEXITY AND SYMMETRIES IN DNA SEQUENCES 95 Carlo Cattani 6 ONTOLOGY-DRIVEN FORMAL CONCEPTUAL DATA MODELING FOR BIOLOGICAL DATA ANALYSIS 129 Catharina Maria Keet 7 BIOLOGICAL DATA INTEGRATION USING NETWORK MODELS 155 Gaurav Kumar and Shoba Ranganathan 8 NETWORK MODELING OF STATISTICAL EPISTASIS 175 Ting Hu and Jason H. Moore 9 GRAPHICAL MODELS FOR PROTEIN FUNCTION AND STRUCTURE PREDICTION 191 Mingjie Tang, Kean Ming Tan, Xin Lu Tan, Lee Sael, Meghana Chitale, Juan Esquivel-Rodrýguez, and Daisuke Kihara PART C: BIOLOGICAL FEATURE EXTRACTION 10 ALGORITHMS AND DATA STRUCTURES FOR NEXT-GENERATION SEQUENCES 225 Francesco Vezzi, Giuseppe Lancia, and Alberto Policriti 11 ALGORITHMS FOR NEXT-GENERATION SEQUENCING DATA 251 Costas S. Iliopoulos and Solon P. Pissis 12 GENE REGULATORY NETWORK IDENTIFICATION WITH QUALITATIVE PROBABILISTIC NETWORKS 281 Zina M. Ibrahim, Alioune Ngom, and Ahmed Y. Tawfik PART D: BIOLOGICAL FEATURE SELECTION 13 COMPARING, RANKING, AND FILTERING MOTIFS WITH CHARACTER CLASSES: APPLICATION TO BIOLOGICAL SEQUENCES ANALYSIS 309 Matteo Comin and Davide Verzotto 14 STABILITY OF FEATURE SELECTION ALGORITHMS AND ENSEMBLE FEATURE SELECTION METHODS IN BIOINFORMATICS 333 Pengyi Yang, Bing B. Zhou, Jean Yee-Hwa Yang, and Albert Y. Zomaya 15 STATISTICAL SIGNIFICANCE ASSESSMENT FOR BIOLOGICAL FEATURE SELECTION: METHODS AND ISSUES 353 Juntao Li, Kwok Pui Choi, Yudi Pawitan, and Radha Krishna Murthy Karuturi 16 SURVEY OF NOVEL FEATURE SELECTION METHODS FOR CANCER CLASSIFICATION 379 Oleg Okun 17 INFORMATION-THEORETIC GENE SELECTION IN EXPRESSION DATA 399 Patrick E. Meyer and Gianluca Bontempi 18 FEATURE SELECTION AND CLASSIFICATION FOR GENE EXPRESSION DATA USING EVOLUTIONARY COMPUTATION 421 Haider Banka, Suresh Dara, and Mourad Elloumi SECTION II BIOLOGICAL DATA MINING PART E: REGRESSION ANALYSIS OF BIOLOGICAL DATA 19 BUILDING VALID REGRESSION MODELS FOR BIOLOGICAL DATA USING STATA AND R 445 Charles Lindsey and Simon J. Sheather 20 LOGISTIC REGRESSION IN GENOMEWIDE ASSOCIATION ANALYSIS 477 Wentian Li and Yaning Yang 21 SEMIPARAMETRIC REGRESSION METHODS IN LONGITUDINAL DATA: APPLICATIONS TO AIDS CLINICAL TRIAL DATA 501 Yehua Li PART F: BIOLOGICAL DATA CLUSTERING 22 THE THREE STEPS OF CLUSTERING IN THE POST-GENOMIC ERA 521 Raffaele Giancarlo, Giosu´e Lo Bosco, Luca Pinello, and Filippo Utro 23 CLUSTERING ALGORITHMS OF MICROARRAY DATA 557 Haifa Ben Saber, Mourad Elloumi, and Mohamed Nadif 24 SPREAD OF EVALUATION MEASURES FOR MICROARRAY CLUSTERING 569 Giulia Bruno and Alessandro Fiori 25 SURVEY ON BICLUSTERING OF GENE EXPRESSION DATA 591 Adelaide Valente Freitas, Wassim Ayadi, Mourad Elloumi, Jose Luis Oliveira, and Jin-Kao Hao 26 MULTIOBJECTIVE BICLUSTERING OF GENE EXPRESSION DATA WITH BIOINSPIRED ALGORITHMS 609 Khedidja Seridi, Laetitia Jourdan, and El-Ghazali Talbi 27 COCLUSTERING UNDER GENE ONTOLOGY DERIVED CONSTRAINTS FOR PATHWAY IDENTIFICATION 625 Alessia Visconti, Francesca Cordero, Dino Ienco, and Ruggero G. Pensa PART G: BIOLOGICAL DATA CLASSIFICATION 28 SURVEY ON FINGERPRINT CLASSIFICATION METHODS FOR BIOLOGICAL SEQUENCES 645 Bhaskar DasGupta and Lakshmi Kaligounder 29 MICROARRAY DATA ANALYSIS: FROM PREPARATION TO CLASSIFICATION 657 Luciano Cascione, Alfredo Ferro, Rosalba Giugno, Giuseppe Pigola, and Alfredo Pulvirenti 30 DIVERSIFIED CLASSIFIER FUSION TECHNIQUE FOR GENE EXPRESSION DATA 675 Sashikala Mishra, Kailash Shaw, and Debahuti Mishra 31 RNA CLASSIFICATION AND STRUCTURE PREDICTION: ALGORITHMS AND CASE STUDIES 685 Ling Zhong, Junilda Spirollari, Jason T. L. Wang, and Dongrong Wen 32 AB INITIO PROTEIN STRUCTURE PREDICTION: METHODS AND CHALLENGES 703 Jad Abbass, Jean-Christophe Nebel, and Nashat Mansour 33 OVERVIEW OF CLASSIFICATION METHODS TO SUPPORT HIV/AIDS CLINICAL DECISION MAKING 725 Khairul A. Kasmiran, Ali Al Mazari, Albert Y. Zomaya, and Roger J. Garsia PART H: ASSOCIATION RULES LEARNING FROM BIOLOGICAL DATA 34 MINING FREQUENT PATTERNS AND ASSOCIATION RULES FROM BIOLOGICAL DATA 737 Ioannis Kavakiotis, George Tzanis, and Ioannis Vlahavas 35 GALOIS CLOSURE BASED ASSOCIATION RULE MINING FROM BIOLOGICAL DATA 761 Kartick Chandra Mondal and Nicolas Pasquier 36 INFERENCE OF GENE REGULATORY NETWORKS BASED ON ASSOCIATION RULES 803 Cristian Andres Gallo, Jessica Andrea Carballido, and Ignacio Ponzoni PART I: TEXT MINING AND APPLICATION TO BIOLOGICAL DATA 37 CURRENT METHODOLOGIES FOR BIOMEDICAL NAMED ENTITY RECOGNITION 841 David Campos, Sergio Matos, and José Luýs Oliveira 38 AUTOMATED ANNOTATION OF SCIENTIFIC DOCUMENTS: INCREASING ACCESS TO BIOLOGICAL KNOWLEDGE 869 Evangelos Pafilis, Heiko Horn, and Nigel P. Brown 39 AUGMENTING BIOLOGICAL TEXT MINING WITH SYMBOLIC INFERENCE 901 Jong C. Park and Hee-Jin Lee 40 WEB CONTENT MINING FOR LEARNING GENERIC RELATIONS AND THEIR ASSOCIATIONS FROM TEXTUAL BIOLOGICAL DATA 919 Muhammad Abulaish and Jahiruddin 41 PROTEIN–PROTEIN RELATION EXTRACTION FROM BIOMEDICAL ABSTRACTS 943 Syed Toufeeq Ahmed, Hasan Davulcu, Sukru Tikves, Radhika Nair, and Chintan Patel PART J: HIGH-PERFORMANCE COMPUTING FOR BIOLOGICAL DATA MINING 42 ACCELERATING PAIRWISE ALIGNMENT ALGORITHMS BY USING GRAPHICS PROCESSOR UNITS 971 Mourad Elloumi, Mohamed Al Sayed Issa, and Ahmed Mokaddem 43 HIGH-PERFORMANCE COMPUTING IN HIGH-THROUGHPUT SEQUENCING 981 Kamer Kaya, Ayat Hatem, Hatice Gulcin Ozer, Kun Huang, and Umit V. Catalyurek 44 LARGE-SCALE CLUSTERING OF SHORT READS FOR METAGENOMICS ON GPUs 1003 Thuy Diem Nguyen, Bertil Schmidt, Zejun Zheng, and Chee Keong Kwoh SECTION III BIOLOGICAL DATA POSTPROCESSING PART K: BIOLOGICAL KNOWLEDGE INTEGRATION AND VISUALIZATION 45 INTEGRATION OF METABOLIC KNOWLEDGE FOR GENOME-SCALE METABOLIC RECONSTRUCTION 1027 Ali Masoudi-Nejad, Ali Salehzadeh-Yazdi, Shiva Akbari-Birgani, and Yazdan Asgari 46 INFERRING AND POSTPROCESSING HUGE PHYLOGENIES 1049 Stephen A. Smith and Alexandros Stamatakis 47 BIOLOGICAL KNOWLEDGE VISUALIZATION 1073 Rodrigo Santamarýa 48 VISUALIZATION OF BIOLOGICAL KNOWLEDGE BASED ON MULTIMODAL BIOLOGICAL DATA 1109 Hendrik Rohn and Falk Schreiber INDEX 1127

The first comprehensive overview of preprocessing, mining, and postprocessing of biological data Molecular biology is undergoing exponential growth in both the volume and complexity of biological data—and knowledge discovery offers the capacity to automate complex search and data analysis tasks. This book presents a vast overview of the most recent developments on techniques and approaches in the field of biological knowledge discovery and data mining (KDD)—providing in-depth fundamental and technical field information on the most important topics encountered. Written by top experts, Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data covers the three main phases of knowledge discovery (data preprocessing, data processing—also known as data mining—and data postprocessing) and analyzes both verification systems and discovery systems. BIOLOGICAL DATA PREPROCESSING Part A: Biological Data ManagementPart B: Biological Data ModelingPart C: Biological Feature ExtractionPart D Biological Feature Selection BIOLOGICAL DATA MINING Part E: Regression Analysis of Biological DataPart F Biological Data ClusteringPart G: Biological Data ClassificationPart H: Association Rules Learning from Biological DataPart I: Text Mining and Application to Biological DataPart J: High-Performance Computing for Biological Data Mining Combining sound theory with practical applications in molecular biology, Biological Knowledge Discovery Handbook is ideal for courses in bioinformatics and biological KDD as well as for practitioners and professional researchers in computer science, life science, and mathematics.