Mathematical Models in Biology: Bringing Mathematics to Life

This document was uploaded by one of our users. The uploader already confirmed that they had the permission to publish it. If you are author/publisher or own the copyright of this documents, please report to us by using this DMCA report form.

Simply click on the Download Book button.

Yes, Book downloads on Ebookily are 100% Free.

Sometimes the book is free on Amazon As well, so go ahead and hit "Search on Amazon"

This book presents an exciting collection of contributions based on the workshop “Bringing Maths to Life” held October 27-29, 2014 in Naples, Italy.  The state-of-the art research in biology and the statistical and analytical challenges facing huge masses of data collection are treated in this Work. Specific topics explored in depth surround the sessions and special invited sessions of the workshop and include genetic variability via differential expression, molecular dynamics and modeling, complex biological systems viewed from quantitative models, and microscopy images processing, to name several.

In depth discussions of the mathematical analysis required to extract insights from complex bodies of biological datasets, to aid development in the field novel algorithms, methods and software tools for genetic variability, molecular dynamics, and complex biological systems are presented in this book.

Researchers and graduate students in biology, life science, and mathematics/statistics will find the content useful as it addresses existing challenges in identifying the gaps between mathematical modeling and biological research. The shared solutions will aid and promote further collaboration between life sciences and mathematics.

Author(s): V. Zazzu, M. B. Ferraro, M. R. Guarracino (eds.)
Publisher: Springer
Year: 2015

Language: English
Pages: 199
Tags: Mathematical and Computational Biology; Life Sciences, general; Linear and Multilinear Algebras, Matrix Theory; Analysis

Front Matter....Pages i-xii
Image Segmentation, Processing and Analysis in Microscopy and Life Science....Pages 1-16
Image Analysis and Classification for High-Throughput Screening of Embryonic Stem Cells....Pages 17-31
Exploiting “Mental” Images in Artificial Neural Network Computation....Pages 33-44
Applying Design of Experiments Methodology to PEI Toxicity Assay on Neural Progenitor Cells....Pages 45-63
A Design of Experiment Approach to Optimize an Image Analysis Protocol for Drug Screening....Pages 65-84
Computational Modeling of miRNA Biogenesis....Pages 85-98
Tunicate Neurogenesis: The Case of the SoxB2 Missing CNE....Pages 99-108
MECP2: A Multifunctional Protein Supporting Brain Complexity....Pages 109-117
DNA Barcode Classification Using General Regression Neural Network with Different Distance Models....Pages 119-132
First Application of a Distance-Based Outlier Approach to Detect Highly Differentiated Genomic Regions Across Human Populations....Pages 133-144
Predicting the Metagenomics Content with Multiple CART Trees....Pages 145-160
A Statistical Approach to Infer 3d Chromatin Structure....Pages 161-171
Basic Exploratory Proteins Analysis with Statistical Methods Applied on Structural Features....Pages 173-187
Modelling of Protein Surface Using Parallel Heterogeneous Architectures....Pages 189-199