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Tade Souaiaia

dblp:65/7391 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2011
0000-0003-3922-1372ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 50% High-performance computing · 50%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis
0.112011
RseqFlow: workflows for RNA-Seq data analysis · Bioinform. 2011
High-performance computing › scientific workflow
scientific workflow execution
0.112011
RseqFlow: workflows for RNA-Seq data analysis · Bioinform. 2011
Distributed systems
workflow management
0.112011
RseqFlow: workflows for RNA-Seq data analysis · Bioinform. 2011
Bioinformatics and computational biology › sequence analysis
read mapping
0.112009
PerM: efficient mapping of short sequencing reads with periodic full sensitive spaced seeds · Bioinform. 2009
Bioinformatics and computational biology
sequence analysis
0.112009
PerM: efficient mapping of short sequencing reads with periodic full sensitive spaced seeds · Bioinform. 2009

Methods — techniques the papers use, named apart from their topics

periodic spaced seeds · 0.1multithreading · 0.1
YearPublicationVenuePosition
2011 RseqFlow: workflows for RNA-Seq data analysis
abstract
SUMMARY: We have developed an RNA-Seq analysis workflow for single-ended Illumina reads, termed RseqFlow. This workflow includes a set of analytic functions, such as quality control for sequencing data, signal tracks of mapped reads, calculation of expression levels, identification of differentially expressed genes and coding SNPs calling. This workflow is formalized and managed by the Pegasus Workflow Management System, which maps the analysis modules onto available computational resources, automatically executes the steps in the appropriate order and supervises the whole running process. RseqFlow is available as a Virtual Machine with all the necessary software, which eliminates any complex configuration and installation steps. AVAILABILITY AND IMPLEMENTATION: http://genomics.isi.edu/rnaseq CONTACT: [email protected]; [email protected]; [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Gaurang Mehta, Rajiv Mayani, Jingxi Lu, Tade Souaiaia, Yangho Chen, Andrew P. Clark, Hee Jae Yoon, Oleg V. Evgrafov, James A. Knowles, Ewa Deelman
Bioinform.5
2009 PerM: efficient mapping of short sequencing reads with periodic full sensitive spaced seeds
abstract
MOTIVATION: The explosion of next-generation sequencing data has spawned the design of new algorithms and software tools to provide efficient mapping for different read lengths and sequencing technologies. In particular, ABI's sequencer (SOLiD system) poses a big computational challenge with its capacity to produce very large amounts of data, and its unique strategy of encoding sequence data into color signals. RESULTS: We present the mapping software, named PerM (Periodic Seed Mapping) that uses periodic spaced seeds to significantly improve mapping efficiency for large reference genomes when compared with state-of-the-art programs. The data structure in PerM requires only 4.5 bytes per base to index the human genome, allowing entire genomes to be loaded to memory, while multiple processors simultaneously map reads to the reference. Weight maximized periodic seeds offer full sensitivity for up to three mismatches and high sensitivity for four and five mismatches while minimizing the number random hits per query, significantly speeding up the running time. Such sensitivity makes PerM a valuable mapping tool for SOLiD and Solexa reads. AVAILABILITY: http://code.google.com/p/perm/
Yangho Chen, Tade Souaiaia
Bioinform.2