Proteogenomic Database Construction Driven from Large Scale RNA-seq Data
نویسندگان
چکیده
منابع مشابه
Investigating the Function of Predicted Proteins from RNA-Seq Data in Holstein and Cholistani Cattle Breeds
This study was performed to determine the digital expression profile of different genes expressed in Holstein and Cholistani breeds as well as to evaluate the performance of predicted proteins derived from differentially expressed genes between these two breeds using RNA-Seq data. For this purpose, the whole mRNA sequence for a blood sample of American Holstein and Pakistani Cholistani cattle p...
متن کاملConstruction and Optimization of a Large Gene Coexpression Network in Maize Using RNA-Seq Data.
With the emergence of massively parallel sequencing, genomewide expression data production has reached an unprecedented level. This abundance of data has greatly facilitated maize research, but may not be amenable to traditional analysis techniques that were optimized for other data types. Using publicly available data, a gene coexpression network (GCN) can be constructed and used for gene func...
متن کاملRNA-seq driven gene identification
The reliable identification of genes is a challenging and crucial part of genome research. Various methods aiming at accurate predictions have evolved that predict genes ab initio on reference sequences or evidence based with help of additional information. With high-throughput RNA-Seq data reflecting currently expressed genes, a particularly meaningful source of information has become commonly...
متن کاملDisease Biomarker Query from RNA-Seq Data
As a revolutionary way to unveil transcription, RNA-Seq technologies are challenging bioinformatics for its large data volumes and complexities. A large number of computational models have been proposed for differential expression (DE) analysis and normalization from different standing points. However, there were no studies available yet to conduct disease biomarker discovery for this type of h...
متن کاملDetecting Sources of Transcriptional Heterogeneity in Large-Scale RNA-Seq Data Sets.
Gene expression levels are dynamic molecular phenotypes that respond to biological, environmental, and technical perturbations. Here we use a novel replicate-classifier approach for discovering transcriptional signatures and apply it to the Genotype-Tissue Expression data set. We identified many factors contributing to expression heterogeneity, such as collection center and ischemia time, and o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Proteome Research
سال: 2013
ISSN: 1535-3893,1535-3907
DOI: 10.1021/pr400294c