Advanced search    

Search: authors:"Jeongsu Oh"

5 papers found.
Use AND, OR, NOT, +word, -word, "long phrase", (parentheses) to fine-tune your search.

CLUSTOM-CLOUD: In-Memory Data Grid-Based Software for Clustering 16S rRNA Sequence Data in the Cloud Environment

High-throughput sequencing can produce hundreds of thousands of 16S rRNA sequence reads corresponding to different organisms present in the environmental samples. Typically, analysis of microbial diversity in bioinformatics starts from pre-processing followed by clustering 16S rRNA reads into relatively fewer operational taxonomic units (OTUs). The OTUs are reliable indicators of...

CLUSTOM: A Novel Method for Clustering 16S rRNA Next Generation Sequences by Overlap Minimization

The recent nucleic acid sequencing revolution driven by shotgun and high-throughput technologies has led to a rapid increase in the number of sequences for microbial communities. The availability of 16S ribosomal RNA (rRNA) gene sequences from a multitude of natural environments now offers a unique opportunity to study microbial diversity and community structure. The large volume...

An integrated database-pipeline system for studying single nucleotide polymorphisms and diseases

Background Studies on the relationship between disease and genetic variations such as single nucleotide polymorphisms (SNPs) are important. Genetic variations can cause disease by influencing important biological regulation processes. Despite the needs for analyzing SNP and disease correlation, most existing databases provide information only on functional variants at specific...

Accurate quantification of transcriptome from RNA-Seq data by effective length normalization

We propose a novel, efficient and intuitive approach of estimating mRNA abundances from the whole transcriptome shotgun sequencing (RNA-Seq) data. Our method, NEUMA (Normalization by Expected Uniquely Mappable Area), is based on effective length normalization using uniquely mappable areas of gene and mRNA isoform models. Using the known transcriptome sequence model such as RefSeq...

Mitome: dynamic and interactive database for comparative mitochondrial genomics in metazoan animals

Mitome is a specialized mitochondrial genome database designed for easy comparative analysis of various features of metazoan mitochondrial genomes such as base frequency, A+T skew, codon usage and gene arrangement pattern. A particular function of the database is the automatic reconstruction of phylogenetic relationships among metazoans selected by a user from a taxonomic tree...