Statistical Genetics & Bioinformatics

Per Page:

Big Data in Omics and Imaging: Association Analysis

Momiao Xiong
December 22, 2017

Big Data in Omics and Imaging: Association Analysis addresses the recent development of association analysis and machine learning for both population and family genomic data in sequencing era. It is unique in that it presents both hypothesis testing and a data mining approach to holistically...

Applied Surrogate Endpoint Evaluation Methods with SAS and R

Ariel Alonso, Theophile Bigirumurame, Tomasz Burzykowski, Marc Buyse, Geert Molenberghs, Leacky Muchene, Nolen Joy Perualila, Ziv Shkedy, Wim Van der Elst
December 13, 2017

An important factor that affects the duration, complexity and cost of a clinical trial is the endpoint used to study the treatment’s efficacy. When a true endpoint is difficult to use because of such factors as long follow-up times or prohibitive cost, it is sometimes possible to use a surrogate...

Gene Expression Studies Using Affymetrix Microarrays

Hinrich Gohlmann, Willem Talloen
November 03, 2017

The Affymetrix GeneChip® system is one of the most widely adapted microarray platforms. However, due to the overwhelming amount of information available, many Affymetrix users tend to stick to the default analysis settings and may end up drawing sub-optimal conclusions. Written by a molecular...

Computational Exome and Genome Analysis

Peter N. Robinson, Rosario Michael Piro, Marten Jager
September 11, 2017

Exome and genome sequencing are revolutionizing medical research and diagnostics, but the computational analysis of the data has become an extremely heterogeneous and often challenging area of bioinformatics. Computational Exome and Genome Analysis provides a practical introduction to all of...

Statistical Portfolio Estimation

Masanobu Taniguchi, Hiroshi Shiraishi, Junichi Hirukawa, Hiroko Kato Solvang, Takashi Yamashita
August 21, 2017

The composition of portfolios is one of the most fundamental and important methods in financial engineering, used to control the risk of investments. This book provides a comprehensive overview of statistical inference for portfolios and their various applications. A variety of asset processes are...

Python for Bioinformatics, Second Edition

Sebastian Bassi
July 10, 2017

In today's data driven biology, programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of...

Microarray Image Analysis: An Algorithmic Approach

Karl Fraser, Zidong Wang, Xiaohui Liu
June 14, 2017

To harness the high-throughput potential of DNA microarray technology, it is crucial that the analysis stages of the process are decoupled from the requirements of operator assistance. Microarray Image Analysis: An Algorithmic Approach presents an automatic system for microarray image processing to...

Meta-analysis and Combining Information in Genetics and Genomics

Rudy Guerra, Darlene R. Goldstein
June 14, 2017

Novel Techniques for Analyzing and Combining Data from Modern Biological StudiesBroadens the Traditional Definition of Meta-Analysis With the diversity of data and meta-data now available, there is increased interest in analyzing multiple studies beyond statistical approaches of formal...

Asymptotic Analysis of Mixed Effects Models: Theory, Applications, and Open Problems

Jiming Jiang
June 08, 2017

Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice....

Algorithms for Next-Generation Sequencing

Wing-Kin Sung
May 24, 2017

Advances in sequencing technology have allowed scientists to study the human genome in greater depth and on a larger scale than ever before – as many as hundreds of millions of short reads in the course of a few days. But what are the best ways to deal with this flood of data? Algorithms for...

Statistical Modeling and Machine Learning for Molecular Biology

Alan Moses
December 15, 2016

Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big-picture concepts...

Applied Biclustering Methods for Big and High-Dimensional Data Using R

Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
October 04, 2016

Proven Methods for Big Data Analysis As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering...