Computational Methods for Data Analysis provides a systematic introduction to the computational, statistical and machine-learning techniques used for analysing complex datasets. The book begins with UNIX and Linux fundamentals before introducing knowledge discovery, data preprocessing, data mining and pattern recognition. It explains important computational approaches such as Hidden Markov Models, artificial neural networks, support vector machines and clustering methods. Statistical techniques, including principal component analysis, ANOVA and AMOVA, are presented alongside their practical applications. Dedicated coverage of gene prediction and phylogenetic algorithms connects computational methods with biological and genetic research. The concluding chapter introduces R programming for data manipulation, visualization and statistical analysis. Designed for students, teachers and researchers, the book develops the interdisciplinary skills required for computational biology, bioinformatics, data science and research-oriented data analysis.

Dr. Archana Rani is currently serving as a Senior Research Fellow in the Department of Plant Breeding and Genetics at Jawaharlal Nehru Krishi Vishwa Vidyalaya (JNKVV), Jabalpur, Madhya Pradesh. She holds both her Master’s and Doctoral degrees in Genetics from Rajendra Prasad Central Agricultural University, Pusa, Samastipur, Bihar, where she was awarded university fellowships for academic excellence throughout her postgraduate studies.

With nearly a decade of professional experience in agricultural research and academics, Dr. Rani has significantly contributed to several key research projects, including a Japan –funded JICA project on the Evaluation of promising soybean genotypes under excessive soil moisture conditions and the ICAR-funded CRP on Hybrid Technology in Wheat. Her teaching and research engagements have also extended to U.P. College (affiliated with LNM University, Darbhanga) and her alma mater in Pusa, Bihar.

A major milestone in her career is her association with the development of the wheat variety MP 3535. Her scholarly contributions are substantial, with over 30 research papers, 19 book chapters, and 27 extension articles published in reputed platforms. She is also the author of the academic book Agricultural Biotechnology – Concept and Practices, which reflects her expertise in the field. In recognition of her scientific contributions, Dr. Rani was honored with the Young Scientist Award at an international symposium held at Sido Kanhu Murmu University, Dumka, Jharkhand. Her active participation in 17 national and international seminars, symposia, and training programs further underscores her commitment to continuous learning and knowledge dissemination in the agricultural sciences.

Chapter 1: Introduction to Computational Data Analysis

Chapter 2: Basics of UNIX and Linux

Chapter 3: Working in UNIX/Linux Environment

Chapter 4: Knowledge Discovery in Databases (KDD)

Chapter 5: Fundamentals of Data Mining

Chapter 6: Introduction to Machine Learning

Chapter 7: Pattern Recognition Techniques

Chapter 8: Hidden Markov Models (HMM)

Chapter 9: Artificial Neural Networks (ANN)

Chapter 10: Support Vector Machines (SVM)

Chapter 11: Principal Component Analysis (PCA)

Chapter 12: Analysis of Variance (ANOVA)

Chapter 13: Analysis of Molecular Variance (AMOVA)

Chapter 14: Clustering Methods

Chapter 15: Gene Prediction and Phylogeny Algorithms

Chapter 16: Introduction to R