Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP
by
Goode, David L.
, Sidow, Arend
, Batzoglou, Serafim
, Cooper, Gregory M.
, Davydov, Eugene V.
, Sirota, Marina
in
Algorithms
/ Animals
/ Binding sites
/ Computational Biology
/ Computational Biology/Comparative Sequence Analysis
/ Computational Biology/Genomics
/ Dynamic programming
/ Evolutionary Biology
/ Evolutionary Biology/Bioinformatics
/ Evolutionary Biology/Evolutionary and Comparative Genetics
/ Evolutionary Biology/Genomics
/ Experiments
/ Fractions
/ Genetic algorithms
/ Genome, Human - genetics
/ Genomes
/ Genomics
/ Genomics - methods
/ Human genome
/ Humans
/ Mammals - genetics
/ Methods
/ Models, Genetic
/ Phylogenetics
/ Phylogeny
/ Sequence Alignment - methods
/ Sequence Analysis, DNA
/ Software
/ Studies
/ User-Computer Interface
2010
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP
by
Goode, David L.
, Sidow, Arend
, Batzoglou, Serafim
, Cooper, Gregory M.
, Davydov, Eugene V.
, Sirota, Marina
in
Algorithms
/ Animals
/ Binding sites
/ Computational Biology
/ Computational Biology/Comparative Sequence Analysis
/ Computational Biology/Genomics
/ Dynamic programming
/ Evolutionary Biology
/ Evolutionary Biology/Bioinformatics
/ Evolutionary Biology/Evolutionary and Comparative Genetics
/ Evolutionary Biology/Genomics
/ Experiments
/ Fractions
/ Genetic algorithms
/ Genome, Human - genetics
/ Genomes
/ Genomics
/ Genomics - methods
/ Human genome
/ Humans
/ Mammals - genetics
/ Methods
/ Models, Genetic
/ Phylogenetics
/ Phylogeny
/ Sequence Alignment - methods
/ Sequence Analysis, DNA
/ Software
/ Studies
/ User-Computer Interface
2010
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP
by
Goode, David L.
, Sidow, Arend
, Batzoglou, Serafim
, Cooper, Gregory M.
, Davydov, Eugene V.
, Sirota, Marina
in
Algorithms
/ Animals
/ Binding sites
/ Computational Biology
/ Computational Biology/Comparative Sequence Analysis
/ Computational Biology/Genomics
/ Dynamic programming
/ Evolutionary Biology
/ Evolutionary Biology/Bioinformatics
/ Evolutionary Biology/Evolutionary and Comparative Genetics
/ Evolutionary Biology/Genomics
/ Experiments
/ Fractions
/ Genetic algorithms
/ Genome, Human - genetics
/ Genomes
/ Genomics
/ Genomics - methods
/ Human genome
/ Humans
/ Mammals - genetics
/ Methods
/ Models, Genetic
/ Phylogenetics
/ Phylogeny
/ Sequence Alignment - methods
/ Sequence Analysis, DNA
/ Software
/ Studies
/ User-Computer Interface
2010
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP
Journal Article
Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP
2010
Request Book From Autostore
and Choose the Collection Method
Overview
Computational efforts to identify functional elements within genomes leverage comparative sequence information by looking for regions that exhibit evidence of selective constraint. One way of detecting constrained elements is to follow a bottom-up approach by computing constraint scores for individual positions of a multiple alignment and then defining constrained elements as segments of contiguous, highly scoring nucleotide positions. Here we present GERP++, a new tool that uses maximum likelihood evolutionary rate estimation for position-specific scoring and, in contrast to previous bottom-up methods, a novel dynamic programming approach to subsequently define constrained elements. GERP++ evaluates a richer set of candidate element breakpoints and ranks them based on statistical significance, eliminating the need for biased heuristic extension techniques. Using GERP++ we identify over 1.3 million constrained elements spanning over 7% of the human genome. We predict a higher fraction than earlier estimates largely due to the annotation of longer constrained elements, which improves one to one correspondence between predicted elements with known functional sequences. GERP++ is an efficient and effective tool to provide both nucleotide- and element-level constraint scores within deep multiple sequence alignments.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
/ Animals
/ Computational Biology/Comparative Sequence Analysis
/ Computational Biology/Genomics
/ Evolutionary Biology/Bioinformatics
/ Evolutionary Biology/Evolutionary and Comparative Genetics
/ Evolutionary Biology/Genomics
/ Genomes
/ Genomics
/ Humans
/ Methods
/ Sequence Alignment - methods
/ Software
/ Studies
MBRLCatalogueRelatedBooks
Related Items
Related Items
This website uses cookies to ensure you get the best experience on our website.