compareprospector.stanford.edu

Compare Prospector

Comparative genomics is a promising approach to the challenging problem of eukaryotic transcription regulatory element identification, since functional non-coding sequences may be conserved across species due to evolutionary constraints. We systematically analyzed known human and. Transcription regulatory elements and discovered that known human regulatory elements are more conserved between human and mouse than background sequences. Though known. S cerevisiae to S. pombe. C elegans–C. briggsae.

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Compare Prospector | compareprospector.stanford.edu Reviews

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Comparative genomics is a promising approach to the challenging problem of eukaryotic transcription regulatory element identification, since functional non-coding sequences may be conserved across species due to evolutionary constraints. We systematically analyzed known human and. Transcription regulatory elements and discovered that known human regulatory elements are more conserved between human and mouse than background sequences. Though known. S cerevisiae to S. pombe. C elegans–C. briggsae.

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3 output

4 reference

5 download

6 supplementary tables

7 bioprospector search

8 about the authors

9 s cerevisiae

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Compare Prospector | compareprospector.stanford.edu Reviews

https://compareprospector.stanford.edu

Comparative genomics is a promising approach to the challenging problem of eukaryotic transcription regulatory element identification, since functional non-coding sequences may be conserved across species due to evolutionary constraints. We systematically analyzed known human and. Transcription regulatory elements and discovered that known human regulatory elements are more conserved between human and mouse than background sequences. Though known. S cerevisiae to S. pombe. C elegans–C. briggsae.

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compareprospector.stanford.edu

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Compare Prospector

http://compareprospector.stanford.edu/inputs.html

1) FASTA: every sequence is written as (see example. The " " is very important here". Sequence as one / more lines [return/s]. CompareProspector recognizes only DNA sequences, either in ATGC. Alphabet. Bases such as N or U are randomly assigned A/T/G/C. Each sequence must be less than 32766 bases long and the total input size must be less than 200KB. Conservation of input sequences: please specify either an alignment file in mfa format or a window percent identity file:. Alignment file in mfa format:.

2

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http://compareprospector.stanford.edu/about.html

Department of Biostatistical Science. Harvard School of Public Health. Dana Farber Cancer Institute. Email: xsliu@jimmy.harvard.edu. These authors contributed equally to the work. College of Life Sciences. Beijing, P.R. China 100871. Email: weilp@mail.cbi.pku.edu.cn. Russ B. Altman. Departments of Genetics and Medicine. Dana Farber Cancer Institute. Email: russ.altman@stanford.edu. Department of Computer Science. Email: serafim@cs.stanford.edu.

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http://compareprospector.stanford.edu/tables.html

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http://compareprospector.stanford.edu/overview.html

We developed CompareProspector to take advantage of comparative genomics information to aid sequence motif finding. CompareProspector is built upon BioProspector (Liu X et al, 2000), which is an extension of the original Gibbs sampler (Liu JS et al, 1995) with improved flexibility and performance. In the Gibbs sampling iterations, CompareProspector biases the motif finding towards sequences conserved across species. First of all, the user can specify two WPID thresholds, T. Is calculated for every site x.

5

Compare Prospector

http://compareprospector.stanford.edu/output.html

The following is a typical. CompareProspector Search Result *. First, the program searches for motifs in a number of runs and the highest-scoring motif from each run is listed:. Try #n; motif score; motif find(and its reverse compliment); number of aligned segments. For example,. Try #19 3.101 CAGCTGTT AACAGCTG 21. The program then reports the number of top motifs you specified. Each motif looks like the following:. The highest scoring 3 motifs are:. Motif width (blk 1, blk 2); Gap [min gap, max gap];.

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compareprospector.stanford.edu

Compare Prospector

Comparative genomics is a promising approach to the challenging problem of eukaryotic transcription regulatory element identification, since functional non-coding sequences may be conserved across species due to evolutionary constraints. We systematically analyzed known human and. Transcription regulatory elements and discovered that known human regulatory elements are more conserved between human and mouse than background sequences. Though known. S cerevisiae to S. pombe. C elegans–C. briggsae.

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