Sciweavers
Explore
Publications
Books
Software
Tutorials
Presentations
Lectures Notes
Datasets
Labs
Conferences
Community
Upcoming
Conferences
Top Ranked Papers
Most Viewed Conferences
Conferences by Acronym
Conferences by Subject
Conferences by Year
Tools
Sci2ools
International Keyboard
Graphical Social Symbols
CSS3 Style Generator
OCR
Web Page to Image
Web Page to PDF
Merge PDF
Split PDF
Latex Equation Editor
Extract Images from PDF
Convert JPEG to PS
Convert Latex to Word
Convert Word to PDF
Image Converter
PDF Converter
Community
Sciweavers
About
Terms of Use
Privacy Policy
Cookies
Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools
7
click to vote
JIB
2008
favorite
Email
discuss
report
60
views
more
JIB 2008
»
Graph-based sequence annotation using a data integration approach
13 years 5 months ago
Download
journal.imbio.de
Robert Pesch, Artem Lysenko, Matthew Hindle, Keywa
Real-time Traffic
JIB 2008
|
claim paper
Related Content
»
Annotation of gene promoters by integrative datamining of ChIPseq PolII enrichment data
»
Hybrid Integration of MolecularBiological Annotation Data
»
Integrating sequence and structural biology with DAS
»
Annotation graphs as a framework for multidimensional linguistic data analysis
»
Flexible Integration of MolecularBiological Annotation Data The GenMapper Approach
»
DISCLOSE DISsection of CLusters Obtained by SEries of transcriptome data using functional...
»
Protein Annotation by Secondary Structure Based Alignments PASSTA
»
miRBase integrating microRNA annotation and deepsequencing data
»
XplorSeq A software environment for integrated management and phylogenetic analysis of met...
more »
Post Info
More Details (n/a)
Added
13 Dec 2010
Updated
13 Dec 2010
Type
Journal
Year
2008
Where
JIB
Authors
Robert Pesch, Artem Lysenko, Matthew Hindle, Keywan Hassani-Pak, Ralf Thiele, Christopher J. Rawlings, Jacob Köhler, Jan Taubert
Comments
(0)
Researcher Info
JIB 2006 Study Group
Computer Vision