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- Towards computational prediction of microRNA function and activity
- An alignment-free method to identify candidate orthologous enhancers in multiple Drosophila genomes
- Genome-wide functional element detection using pairwise statistical alignment outperforms multi-genome footprinting techniques
- Mining metabolic pathways through gene expression
- Integration of pathway knowledge into a weighted recursive feature elimination approach for cancer patients risk stratification
- Identifying compositionally homogeneous and nonhomogeneous domains within the human genome using a novel segmentation algorithm
- A Poisson model for random multigraphs
- A Bayesian approach using covariance of SNP data to detect differences in linkage disequilibrium patterns between groups
- Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor
- Over-optimism in bioinformatics: an illustration
Nucleic Acids Research
- Identifying compositionally homogeneous and nonhomogeneous domains within the human genome using a novel segmentation algorithm
- A flexible and efficient template format for circular consensus sequencing and SNP detection
- Towards computational prediction of microRNA function and activity
- Zinc-finger nuclease-driven targeted integration into mammalian genomes using donors with limited chromosomal homology
- The synthetic integron: an in vivo genetic shuffling device
Bioinformatics
- An alignment-free method to identify candidate orthologous enhancers in multiple Drosophila genomes
- Genome-wide functional element detection using pairwise statistical alignment outperforms multiple genome footprinting techniques
- First insight into the prediction of protein folding rate change upon point mutation
- Mining metabolic pathways through gene expression
- Integration of pathway knowledge into a reweighted recursive feature elimination approach for risk stratification of cancer patients
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inGAP: an integrated next-generation genome analysis pipeline
Submitted by bogdan on Tue, 2009-12-29 23:32inGAP: an integrated next-generation genome analysis pipeline - Summary: We develop a novel mining pipeline, Integrative Next-generation Genome Analysis Pipeline (inGAP), guided by a Bayesian principle to detect single nucleotide polymorphisms (SNPs), insertion/deletions (indels) by comparing high-throughput pyrosequencing reads with a reference genome of related organisms. inGAP can be applied to the mapping of both Roche/454 and Illumina reads with no restriction of read length. Experiments on simulated and experimental data show that this pipeline can achieve overall 97% accuracy in SNP detection and 94% in the finding of indels. All the detected SNPs/indels can be further evaluated by a graphical editor in our pipeline. inGAP also provides functions of multiple genomes comparison and assistance of bacterial genome assembly.
Availability: inGAP is available at http://sites.google.com/site/nextgengenomics/ingap