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Thursday, April 23, 2020 | History

3 edition of Computational and Evolutionary Analysis of HIV Molecular Sequences found in the catalog.

Computational and Evolutionary Analysis of HIV Molecular Sequences

  • 104 Want to read
  • 19 Currently reading

Published by Springer .
Written in English

    Subjects:
  • HIV / AIDS,
  • Research,
  • Life Sciences - Biology - Microbiology,
  • Aids (Acquired Immune Deficiency Syndrome),
  • Viral Genetics,
  • Science,
  • Medical / Nursing,
  • Nucleotide sequence,
  • Medical,
  • Methodology,
  • AIDS & HIV,
  • Infectious Diseases,
  • Medical / AIDS & HIV,
  • Medical / Internal Medicine,
  • Medical : Infectious Diseases,
  • Medical : Research,
  • Retroviruses,
  • Genetics,
  • HIV (Viruses)

  • Edition Notes

    ContributionsAllen G. Rodrigo (Editor), Gerald H. Learn Jr. (Editor)
    The Physical Object
    FormatHardcover
    Number of Pages312
    ID Numbers
    Open LibraryOL7810046M
    ISBN 100792379942
    ISBN 109780792379942

    Analysis of molecular sequence data is the main subject of this introduction to computational biology. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space inBrand: Birkhäuser Basel.


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Computational and Evolutionary Analysis of HIV Molecular Sequences Download PDF EPUB FB2

About this book. Introduction. Computational and Evolutionary Analysis of HIV Molecular Sequences is for all researchers interested in HIV research, even those who only have a nodding acquaintance with computational biology (or those who are Computational and Evolutionary Analysis of HIV Molecular Sequences book.

Computational and Evolutionary Analysis of HIV Molecular Sequences is for all researchers interested in HIV research, even those who only have a nodding acquaintance with computational biology (or those who are familiar with some, but not all, aspects of the field).

HIV research is unusual in that it brings together scientists from a wide range of disciplines: clinicians, pathologists, immunologists, epidemiologists, virologists, computational biologists Brand: Springer US.

Computational and Evolutionary Analysis of HIV Molecular Sequences is for all researchers interested in HIV research, even those who only have a nodding acquaintance with computational biology (or those who are familiar with some, but not all, aspects of the field).

HIV research is unusual in that it brings together scientists from a wide range of disciplines: clinicians, pathologists, immunologists, epidemiologists, virologists, computational biologists Brand: Springer US. Summary: "Computational and Evolutionary Analysis of HIV Molecular Sequences is for all researchers invested in HIV research, even those who only have a nodding acquaintance with computational biology (or those who are familiar with some, but not all, aspects of the field).

Computational and Evolutionary Analysis of HIV Molecular Sequences is for all researchers interested in HIV research, even those who only have a nodding acquaintance with computational biology (or those who are familiar with some, but not all, aspects of the field).

Computational and Evolutionary Analysis of HIV Molecular Sequences covers such issues as sampling and processing sequences, population genetics, phylogenetics and drug targets.

Ignore positive goal layout that start doing the wrong cats in each population. This was both significant and enlightening and encouragement. E-BOOK EXCERPT. Computational and Evolutionary Analysis of HIV Molecular Sequences is for all researchers interested in HIV research, even those who only have a nodding acquaintance with computational biology (or those who are familiar with some, but not all, aspects of the field).

Computational and Evolutionary Analysis of HIV Molecular Sequences pp | Cite as Sampling and Processing HIV Molecular Sequences: A Computational Evolutionary Biologist’s Cited by: Despite the proliferation of increasingly sophisticated models of DNA sequence evolution, choosing among models remains a major problem in phylogenetic reconstruction.

The choice of appropriate models is thought to be especially important when there is large variation among branch lengths. Computational Molecular Evolution provides an up-to-date and comprehensive coverage of modern statistical and computational methods used in molecular evolutionary analysis, such as maximum likelihood and Bayesian statistics.

Yang Computational and Evolutionary Analysis of HIV Molecular Sequences book the models, methods and algorithms that are most useful for analysing Author: Ziheng Yang.

Evolutionary analysis of hepatitis C virus gene sequences from Rebecca R. Gray1, such as rates of molecular evolution, dates and locations of epidemic origin and past rates of transmission [2]. For HIV-1, the utility of historical isolates was demon- HCV transmission before has come from the evolutionary analysis of virus gene.

Description: Computational and Evolutionary Analysis of HIV Molecular Sequences is for all researchers interested in HIV research, even those who only have a nodding acquaintance with computational biology (or those who are familiar with some, but not all, aspects of the field).

Sampling and processing HIV molecular sequences: a computational evolutionary biologist’s perspective. In Computational and Evolutionary Analysis of HIV Molecular Sequences (eds. Rodrigo and G. Learn). Computational Molecular Evolution provides an up-to-date and comprehensive coverage of modern statistical and computational methods used in molecular evolutionary analysis, such as maximum likelihood and Bayesian statistics.

Yang describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of Cited by:   Maljkovic Berry, I.

et al. Unequal evolutionary rates in the human immunodeficiency virus type 1 (HIV-1) pandemic: the evolutionary rate of HIV-1 Cited by: Computational Molecular Evolution Ziheng Yang Oxford Series in Ecology and Evolution. Computational Molecular Evolution provides an up-to-date and comprehensive coverage of modern statistical and computational methods used in molecular evolutionary analysis, such as maximum likelihood and Bayesian statistics.

Yang describes the models, methods and algorithms that are most. information. Molecular Evolutionary Genetic Analysis (MEGA) is user friendly bio-computational software for sequence analysis and phylogenetic analysis.

MEGA developed with the aim to bridge the gap between wet lab result and significance that can characterize by nucleotide and amino acid to produce scoring and evolutionary relationship.

When sequences are paired with their sampling times, it becomes possible to calibrate molecular phylogenies of pathogen sequences and infer the timing of pathogen evolution.

For example, HIV-1 sequences have been sampled at various times and geographic locations following its initial characterization in [ 2, 9, 10 ].Author: Sayaka Miura, Koichiro Tamura, Qiqing Tao, Louise A.

Huuki, Sergei L. Kosakovsky Pond, Jessica Pries. The HIV virus is known for its ability to exploit numerous genetic and evolutionary mechanisms to ensure its proliferation, among them, high replication, mutation and recombination rates.

Sliding MinPD, a recently introduced computational method [1], was used to investigate the patterns of evolution of serially-sampled HIV-1 sequence data from eight patients with a special focus on the Cited by: 2. Sequence alignments are essential for phylogenetic analysis tracing the epidemiology of HIV, but also for interpretations of drug resistance and data mining efforts, where correctly positioning nucleotides or amino acids of different strains with respect to each other is pivotal.

Determination of the molecular evolution of hepatitis B virus (HBV) involves an understanding of the accumulated sequence changes to the viral genome and the observed mutation rate over a long by: Computational Genome Analysis: An Introduction presents the foundations of key problems in computational molecular biology and bioinformatics.

It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these by:   Abstract.

The Molecular Evolutionary Genetics Analysis (MEGA) software is a desktop application designed for comparative analysis of homologous gene sequences either from multigene families or from different species with a special emphasis on inferring evolutionary relationships and patterns of DNA and protein by: The author's research in molecular genetics, evolution, and bio-mathematics has enabled him to draw on this work, and present a coherent and valuable view of the field.

The book is divided into three parts. The first consists of three chapters on protein evolution, DNA evolution, and molecular mechanisms.

Computational Molecular Evolution provides an up-to-date and comprehensive coverage of modern statistical and computational methods used in molecular evolutionary analysis, such as maximum likelihood and Bayesian statistics. Yang describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of.

BEAST 2 is a cross-platform program for Bayesian phylogenetic analysis of molecular sequences. It estimates rooted, time-measured phylogenies using strict or relaxed molecular clock models.

It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree. Author summary Bayesian phylogenetic inference methods have undergone considerable development in recent years, and joint modelling of rich evolutionary data, including genomes, phenotypes and fossil occurrences is increasingly common.

Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have Cited by: The selection mapping algorithm QUASI was used to analyze the avian and human HA sequences isolated during – to determine positively selected sites.

As a result, 33 and 34 PS sites were found throughout avian and human HA sequences, respectively (Figure 1; Table 1, Table 2).Some of the identified PS sites were reported in earlier studies, Cited by: Access to antiretroviral therapy is increasing globally and drug resistance evolution is anticipated.

Currently, protease (PR) and reverse transcriptase (RT) sequence generation is increasing, including the use of in-house sequencing assays, and quality assessment prior to sequence analysis is by: This book seeks to bridge the gap between these groups, in both subject matter and terminology.

Focused largely on HIV genetic variation, Computational and Evolutionary Analysis of HIV Molecular Sequences covers such issues as sampling and processing sequences, population genetics, phylogenetics and drug targets.

Evolutionary Genomics: Statistical and Computational Methods is intended to bring together the more recent developments in the statistical methodology and the challenges that followed as a result of rapidly improving sequencing technologies.

Presented by top scientists from a variety of disciplines, the collection includes a wide spectrum of. Genome Introduction to Computational Molecular Biology: Genome and Protein Sequence Analysis (Winter Quarter ) Synopsis: Together with Genomea two-quarter introduction to protein and DNA sequence analysis and molecular evolution, including probabilistic models of sequences and of sequence evolution, computational gene identification, pairwise sequence.

The study of HIV evolution is not only critical to fighting the virus; it has also driven advances in the computational tools used to study evolution in general.

“Lots of tools have been developed to do evolutionary analysis of gene sequences. Data Analysis in Molecular Biology and Evolution introduces biologists to DAMBE, a proprietary, user-friendly computer program for molecular data analysis. The unique combination of this book and software will allow biologists not only to understand the rationale behind a variety of computational tools in molecular biology and evolution, but.

molecular sequence (DNA and protein sequences) and pairwise distance data. Both could specify domains and genes for multi-gene comparative sequence analysis and could create groups of sequences that would facilitate the estimation of within- and among- group diversities and infer the higher-level evolutionary relationships of genes and species.

Human immunodeficiency virus-1 (HIV-1) is characterised by a vast genetic diversity classified into distinct phylogenetic strains and recombinant forms. We describe the HIV-1 molecular epidemiology and evolution of consecutive HIV-1 positive migrants living in Milan (northern Italy).Author: Sagnelli C, Uberti-Foppa C, Bagaglio S, Cella E, Scolamacchia, Hasson H, Salpietro S, Messina E, Mor.

The field of molecular evolution has experienced explosive growth in recent years due to the rapid accumulation of genetic sequence data, continuous improvements to computer hardware and software, and the development of sophisticated analytical methods.

The increasing availability of large genomic data sets requires powerful statistical methods to analyse and interpret them, generating both. The Bioinformatics and Computational Biosciences Branch (BCBB) offers a suite of scientific services and resources for the NIAID research community and its collaborators.

BCBB provides expertise and computational solutions to researchers at all levels of experience. Computational biologists collaborate on projects using a wide variety of techniques and approaches, and offer consultation and.

Viral evolution and molecular epidemiology – evolving viruses and evolving analysis techniques Viral evolution and molecular epidemiology – evolving viruses and evolving analysis techniques The discipline of molecular phylogeny initiated more than 30 years ago by demonstrating that protein and DNA sequences could be used to reconstruct evolutionary history.

Publications. and Y. Wang. Population genetics of HIV: parameter estimation using genealogy-based methods. Computational and Evolutionary Analysis of HIV Molecular Sequences. Pp In: Computational and Evolutionary Analysis of HIV Molecular Sequences.

Eds. Rodrigo and G. Learn. Kluwer Academic Publishers, Boston. pp. Cambridge Core - Evolutionary Biology - Bayesian Evolutionary Analysis with BEAST - by Alexei J. Drummond from those using phylogenetic tools, to computational biologists and Bayesian statisticians. ‘Inference of viral evolutionary rates from molecular sequences Cited by: Computational phylogenetics is the application of computational algorithms, methods, and programs to phylogenetic analyses.

The goal is to assemble a phylogenetic tree representing a hypothesis about the evolutionary ancestry of a set of genes, species, or other example, these techniques have been used to explore the family tree of hominid species and the relationships between.This book provides a comprehensive coverage of modern statistical and computational methods used in molecular evolutionary analysis, such as maximum likelihood and Bayesian statistics.

It describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of molecular sequence data, with a view to Author: Ziheng Yang.