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
9
click to vote
BIOCOMP
2006
favorite
Email
discuss
report
95
views
Bioinformatics
»
more
BIOCOMP 2006
»
Space-Efficient Parallel Algorithms for the Constrained Multiple Sequence Alignment Problem
13 years 6 months ago
Download
ww1.ucmss.com
Dan He, Abdullah N. Arslan
Real-time Traffic
BIOCOMP 2006
|
BIOCOMP 2007
|
claim paper
Related Content
»
FastPCMSA An Improved Parallel Algorithm for the Constrained Multiple Sequence Alignment P...
»
Algorithms for Loosely Constrained Multiple Sequence Alignment
»
An Evolutionary Algorithm for the Maximum Weight Trace Formulation of the Multiple Sequenc...
»
Efficient Parallel Algorithm for Optimal ThreeSequences Alignment
»
On the design of highperformance algorithms for aligning multiple protein sequences on mes...
»
Multiple sequence alignment by quantum genetic algorithm
»
ClustalXeed a GUIbased grid computation version for high performance and terabyte size mul...
»
Modeling sequence and function similarity between proteins for protein functional annotati...
»
Accelerated probabilistic inference of RNA structure evolution
more »
Post Info
More Details (n/a)
Added
30 Oct 2010
Updated
30 Oct 2010
Type
Conference
Year
2006
Where
BIOCOMP
Authors
Dan He, Abdullah N. Arslan
Comments
(0)
Researcher Info
Bioinformatics Study Group
Computer Vision