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  1. Proceedings of the 5th international workshop on Bioinformatics (BIOKDD '05)
  2. siRNA off-target search: a hybrid q-gram based filtering approach
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Motif discovery for proteins using subsequence clustering
Predicting cancer susceptibility from single-nucleotide polymorphism data: a case study in multiple myeloma
Accelerating DNA sequencing-by-hybridization with noise
Analysis of protein-protein interaction networks using random walks
Graphical models of residue coupling in protein families
On discovery of maximal confident rules without support pruning in microarray data
Finding cliques in protein interaction networks via transitive closure of a weighted graph
A datamining approach to cell population deconvolution from gene expressions using particle filters
Boosting performance of bio-entity recognition by combining results from multiple systems
siRNA off-target search: a hybrid q-gram based filtering approach

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siRNA off-target search: a hybrid q-gram based filtering approach

Content Provider ACM Digital Library
Author Lane, Terran Zhao, Wenzhong
Abstract Designing highly effective and gene-specific short interfering RNA (siRNA) sequences is crucial for any biological applications involving RNA interference (RNAi). A critical requirement for applying RNAi process in therapeutic applications is the ability to predict and to avoid side effect interactions with unintended transcripts (messager RNA, or mRNA). In this paper, we propose a flexible framework for detecting siRNA off-target effects. The framework can also be extended with minor changes to other applications such as selecting PCR primers or microarray nucleotide probes.Based on the framework, we have developed and implemented a new homology sequence search program -- siRNA Off-target Search (SOS). SOS uses a hybrid, q-gram based approach, combining two filtering techniques using overlapping and non-overlapping q-grams. This approach considers three types of imperfect matches based on biological experiments: G:U wobbles, mismatches, and bulges. The three main improvements over existing methods are: 1) introduce a more general cost model (an affine bulge cost model) for siRNA-mRNA off-target alignment; 2) use separate searches for alignments with and without bulges that enables efficient discovery of potential off-target candidates in the filtration phase; and 3) achieve better performance, in terms of speed and recall/precision, than BLAST in detecting potential siRNA off-targets.
Starting Page 54
Ending Page 60
Page Count 7
File Format PDF
ISBN 1595932135
DOI 10.1145/1134030.1134040
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2005-08-21
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Sirna off-target search Sequence alignment Rna interference Approximate pattern matching
Content Type Text
Resource Type Article
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