Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput Data

Advanced data analysis in neuroscience :

📁 Advanced data analysis in neuroscience : integrating statistical and computational models

✍ Durstewitz, Daniel 📂 Library 📅 2017 🏛 Springer 🌐 English

This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost a

Advanced Data Analysis in Neuroscience.

📁 Advanced Data Analysis in Neuroscience. Integrating Statistical and Computational Models

✍ Daniel Durstewitz 📂 Library 📅 2017 🏛 Springer 🌐 English

Bioinformatics for High Throughput Seque

📁 Bioinformatics for High Throughput Sequencing

✍ Naiara Rodríguez-Ezpeleta, Ana M. Aransay (auth.), Naiara Rodríguez-Ezpeleta, Mi 📂 Library 📅 2012 🏛 Springer-Verlag New York 🌐 English

Next generation sequencing is revolutionizing molecular biology. Owing to this new technology it is now possible to carry out a panoply of experiments at an unprecedented low cost and high speed. These go from sequencing whole genomes, transcriptomes and small non-coding RNAs to description of

Bioinformatics for High Throughput Seque

📁 Bioinformatics for High Throughput Sequencing

✍ Naiara Rodríguez-Ezpeleta, Ana M. Aransay (auth.), Naiara Rodríguez-Ezpeleta, Mi 📂 Library 📅 2012 🏛 Springer-Verlag New York 🌐 English

Next generation sequencing is revolutionizing molecular biology. Owing to this new technology it is now possible to carry out a panoply of experiments at an unprecedented low cost and high speed. These go from sequencing whole genomes, transcriptomes and small non-coding RNAs to description of

Regression Models for Data Science in R:

📁 Regression Models for Data Science in R: Statistical inference for data science.

✍ YASSINE MOUSAIF 📂 Library 📅 2022 🏛 UNKNOWN 🌐 English

What's Special about this Book: The ideal reader for this book will be quantitatively literate and has a basic understanding of statistical concepts and R programming. The student should have a basic understanding of statistical inference such as contained in "Statistical infe

Advances in Statistical Models for Data

📁 Advances in Statistical Models for Data Analysis

✍ Isabella Morlini, Tommaso Minerva, Maurizio Vichi (eds.) 📂 Library 📅 2015 🏛 Springer International Publishing 🌐 English

This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas suc