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E-raamat: Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data

Edited by (University of Tunis El Manar, Tunisia), Series edited by (Department of Computer Science, Georgia State University), Edited by (University of Western Australia)
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"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. It surveys the latest approaches and techniques in biological KDD, presenting a vast yet detailed view of the most important advances in the field. Combining sound theory, technical depth, and practical applications in molecular biology, Biological Knowledge Discovery is aunique resource for practitioners and researchers in computer science, life science, and mathematics"--

"This book is a survey of the most recent developments on techniques and approaches in the field of biological KDD. It presents the latest, newest, most important topics encountered in this field"--



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 Management
  • Part B: Biological Data Modeling
  • Part C: Biological Feature Extraction
  • Part D Biological Feature Selection

BIOLOGICAL DATA MINING

  • Part E: Regression Analysis of Biological Data
  • Part F Biological Data Clustering
  • Part G: Biological Data Classification
  • Part H: Association Rules Learning from Biological Data
  • Part I: Text Mining and Application to Biological Data
  • Part 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.

Arvustused

This book is a unique resource for practitioners and researchers in computer science, life science, and  mathematics.  (Zentralblatt MATH, 1 June 2015)

 

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(30)
Bahar Taneri
Terry Gaasterland
2 Cleaning, Integrating, and Warehousing Genomic Data From Biomedical Resources
35(24)
Fouzia Moussouni
Laure Berti-Equille
3 Cleansing of Mass Spectrometry Data for Protein Identification And Quantification
59(18)
Penghao Wang
Albert Y. Zomaya
4 Filtering Protein--Protein Interactions by Integration of Ontology Data
77(18)
Young-Rae Cho
PART B BIOLOGICAL DATA MODELING
5 Complexity and Symmetries in DNA Sequences
95(34)
Carlo Cattani
6 Ontology-Driven Formal Conceptual Data Modeling for Biological Data Analysis
129(26)
Catharina Maria Keet
7 Biological Data Integration Using Network Models
155(20)
Gaurav Kumar
Shoba Ranganathan
8 Network Modeling Of Statistical Epistasis
175(16)
Ting Hu
Jason H. Moore
9 Graphical Models For Protein Function and Structure Prediction
191(34)
Mingjie Tang
Kean Ming Tan
Xin Lu Tan
Lee Sael
Meghana Chitale
Juan Esquivel-Rodriguez
Daisuke Kihara
PART C BIOLOGICAL FEATURE EXTRACTION
10 Algorithms And Data Structures for Next-Generation Sequences
225(26)
Francesco Vezzi
Giuseppe Lancia
Alberto Policriti
11 Algorithms For Next-Generation Sequencing Data
251(30)
Costas S. Iliopoulos
Solon P. Pissis
12 Gene Regulatory Network Identification With Qualitative Probabilistic Networks
281(28)
Zina M. Ibrahim
Alioune Ngom
Ahmed Y. Tawfik
PART D BIOLOGICAL FEATURE SELECTION
13 Comparing, Ranking, and Filtering Motifs With Character Classes: Application to Biological Sequences Analysis
309(24)
Matteo Comin
Davide Verzotto
14 Stability of Feature Selection Algorithms and Ensemble Feature Selection Methods in Bioinformatics
333(20)
Pengyi Yang
Bing B. Zhou
Jean Yee-Hwa Yang
Albert Y. Zomaya
15 Statistical Significance Assessment for Biological Feature Selection: Methods And Issues
353(26)
Juntao Li
Kwok Pui Choi
Yudi Pawitan
Radha Krishna Murthy Karuturi
16 Survey Of Novel Feature Selection Methods for Cancer Classification
379(20)
Oleg Okun
17 Information-Theoretic Gene Selection in Expression Data
399(22)
Patrick E. Meyer
Gianluca Bontempi
18 Feature Selection and Classification for Gene Expression Data Using Evolutionary Computation
421(24)
Haider Banka
Suresh Dara
Mourad Elloumi
SECTION II Biological Data Mining
PART E REGRESSION ANALYSIS OF BIOLOGICAL DATA
19 Building Valid Regression Models for Biological Data Using Stata R
445(32)
Charles Lindsey
Simon J. Sheather
20 Logistic Regression in Genomewide Association Analysis
477(24)
Wentian Li
Yaning Yang
21 Semiparametric Regression Methods in Longitudinal Data: Applications to Aids Clinical Trial Data
501(20)
Yehua Li
PART F BIOLOGICAL DATA CLUSTERING
22 The Three Steps of Clustering in The Post-Genomic Era
521(36)
Raffaele Giancarlo
Giosue Lo Bosco
Luca Pinello
Filippo Utro
23 Clustering Algorithms of Microarray Data
557(12)
Haifa Ben Saber
Mourad Elloumi
Mohamed Nadif
24 Spread of Evaluation Measures for Microarray Clustering
569(22)
Giulia Bruno
Alessandro Fiori
25 Survey on Biclustering of Gene Expression Data
591(18)
Adelaide Valente Freitas
Wassim Ayadi
Mourad Elloumi
Jose Luis Oliveira
Jin-Kao Hao
26 Multiobjective Biclustering of Gene Expression Data With Bioinspired Algorithms
609(16)
Khedidja Seridi
Laetitia Jourdan
El-Ghazali Talbi
27 Coclustering Under Gene Ontology Derived Constraints for Pathway Identification
625(20)
Alessia Visconti
Francesca Cordero
Dino Ienco
Ruggero G. Pensa
PART G BIOLOGICAL DATA CLASSIFICATION
28 Survey On Fingerprint Classification Methods for Biological Sequences
645(12)
Bhaskar DasGupta
Lakshmi Kaligounder
29 Microarray Data Analysis: From Preparation to Classification
657(18)
Luciano Cascione
Alfredo Ferro
Rosalba Giugno
Giuseppe Pigola
Alfredo Pulvirenti
30 Diversified Classifier Fusion Technique for Gene Expression Data
675(10)
Sashikala Mishra
Kailash Shaw
Debahuti Mishra
31 RNA Classification and Structure Prediction: Algorithms and Case Studies
685(18)
Ling Zhong
Junilda Spirollari
Jason T. L. Wang
Dongrong Wen
32 Ab Initio Protein Structure Prediction: Methods and Challenges
703(22)
Jad Abbass
Jean-Christophe Nebel
Nashat Mansour
33 Overview of Classification Methods to Support HIV/Aids Clinical Decision Making
725(12)
Khairul A. Kasmiran
Ali Al Mazari
Albert Y. Zomaya
Roger J. Garsia
PART H ASSOCIATION RULES LEARNING FROM BIOLOGICAL DATA
34 Mining Frequent Patterns and Association Rules From Biological Data
737(24)
Ioannis Kavakiotis
George Tzanis
Ioannis Vlahavas
35 Galois Closure Based Association Rule Mining From Biological Data
761(42)
Kartick Chandra Mondal
Nicolas Pasquier
36 Inference of Gene Regulatory Networks Based on Association Rules
803(38)
Cristian Andres Gallo
Jessica Andrea Carballido
Ignacio Ponzoni
PART I TEXT MINING AND APPLICATION TO BIOLOGICAL DATA
37 Current Methodologies for Biomedical Named Entity Recognition
841(28)
David Campos
Sergio Matos
Jose Luis Oliveira
38 Automated Annotation of Scientific Documents: Increasing Access To Biological Knowledge
869(32)
Evangelos Pafilis
Heiko Horn
Nigel P. Brown
39 Augmenting Biological Text Mining With Symbolic Inference
901(18)
Jong C. Park
Hee-Jin Lee
40 Web Content Mining for Learning Generic Relations and Their Associations From Textual Biological Data
919(24)
Muhammad Abulaish
Jahiruddin
41 Protein--Protein Relation Extraction From Biomedical Abstracts
943(28)
Syed Toufeeq Ahmed
Hasan Davulcu
Sukru Tikves
Radhika Nair
Chintan Patel
PART J HIGH-PERFORMANCE COMPUTING FOR BIOLOGICAL DATA MINING
42 Accelerating Pairwise Alignment Algorithms by Using Graphics Processor Units
971(10)
Mourad Elloumi
Mohamed Al Sayed Issa
Ahmed Mokaddem
43 High-Performance Computing in High-Throughput Sequencing
981(22)
Kamer Kaya
Ayat Hatem
Hatice Gulcin Ozer
Kun Huang
Umit V. Catalyurek
44 Large-Scale Clustering of Short Reads for Metagenomics on GPUs
1003(24)
Thuy Diem Nguyen
Bertil Schmidt
Zejun Zheng
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(22)
Ali Masoudi-Nejad
Ali Salehzadeh-Yazdi
Shiva Akbari-Birgani
Yazdan Asgari
46 Inferring and Postprocessing Huge Phylogenies
1049(24)
Stephen A. Smith
Alexandros Stamatakis
47 Biological Knowledge Visualization
1073(36)
Rodrigo Santamaria
48 Visualization of Biological Knowledge Based on Multimodal Biological Data
1109(18)
Hendrik Rohn
Falk Schreiber
Index 1127
MOURAD ELLOUMI is a Full Professor in Computer Science at the University of Tunis-El Manar, Tunisia. He is the author/coauthor of more than fifty publications in international journals and conference proceedings and the coeditor, along with Albert Zomaya, of Algorithms in Computational Molecular Biology: Techniques, Approaches and Applications (Wiley).

ALBERT Y. ZOMAYA is the Chair Professor of High Performance Computing & Networking at The University of Sydney's School of Information Technologies. He is the author/coauthor of seven books, more than 450 publications in technical journals and conference proceedings, and the editor of fourteen books and nineteen conference volumes. He is a Fellow of the IEEE, the American Association for the Advancement of Science, and IET (UK).
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