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The cost of high throughput DNA sequencing has reduced drastically from around $100 million/human genome in 2001 to around $1000/human genome in 2017. [3] Due to this increase in accessibility, high throughput DNA sequencing has become more widely used in research and clinical settings.
Salmon is a software tool for computing transcript abundance from RNA-seq data using either an alignment-free (based directly on the raw reads) or an alignment-based (based on pre-computed alignments) approach. It uses an online stochastic optimization approach to maximize the likelihood of the transcript abundances under the observed data.
Automated software package to annotate eukaryotic genes from RNA-Seq data and associated protein sequences Eukaryotes [1] FragGeneScan: Predicting genes in complete genomes and sequencing Reads: Prokaryotes, Metagenomes [2] ATGpr: Identifies translational initiation sites in cDNA sequences: Human [3] Prodigal
The GenBank sequence database is an open access, annotated collection of all publicly available nucleotide sequences and their protein translations. It is produced and maintained by the National Center for Biotechnology Information (NCBI; a part of the National Institutes of Health in the United States) as part of the International Nucleotide Sequence Database Collaboration (INSDC).
GeneNetwork is a combined database and open-source bioinformatics data analysis software resource for systems genetics. [1] This resource is used to study gene regulatory networks that link DNA sequence differences to corresponding differences in gene and protein expression and to variation in traits such as health and disease risk.
Open source software provides a platform for computational biology where everyone can access and benefit from software developed in research. PLOS cites [citation needed] four main reasons for the use of open source software: Reproducibility: This allows for researchers to use the exact methods used to calculate the relations between biological ...
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KEGG (Kyoto Encyclopedia of Genes and Genomes) is a collection of databases dealing with genomes, biological pathways, diseases, drugs, and chemical substances.KEGG is utilized for bioinformatics research and education, including data analysis in genomics, metagenomics, metabolomics and other omics studies, modeling and simulation in systems biology, and translational research in drug development.