LGC statistics

info info

Citations per year

Number of citations per year for the bioinformatics software tool LGC
info

Tool usage distribution map

info info

Associated diseases

info

Popular tool citations

chevron_left LncRNA prediction chevron_right
Want to access the full stats & trends on this tool?

LGC specifications

Information


Unique identifier OMICS_29815
Name LGC
Alternative name ORF Length and GC content
Interface Web user interface
Restrictions to use None
Input format FASTA,BED,GTF
Computer skills Basic
Stability Stable
Maintained Yes

Maintainers


  • person_outline Zhang Zhang
  • person_outline Lina Ma

Additional information


http://bigd.big.ac.cn/biocode/tools/BT000004/manual

Information


Unique identifier OMICS_29815
Name LGC
Alternative name ORF Length and GC content
Software type Application/Script
Interface Command line interface
Restrictions to use None
Input format FASTA,BED,GTF
Operating system Unix/Linux
Programming languages Java, Python
Computer skills Advanced
Version 1.0
Stability Stable
Maintained Yes

Download


download.png

Versioning


No version available

Maintainers


  • person_outline Zhang Zhang
  • person_outline Lina Ma

Additional information


http://bigd.big.ac.cn/biocode/tools/BT000004/manual

Publication for ORF Length and GC content

LGC citations

 (3)
library_books

Gene Prediction in Metagenomic Fragments with Deep Learning

2017
Biomed Res Int
PMCID: 5698827
PMID: 29250541
DOI: 10.1155/2017/4740354

[…] FragGeneScan []. Orphelia [, ] firstly extracts the features of monocodon usage, dicodon usage, and translation initiation sites by building linear discriminants and then combines these features with ORF length and GC-content by using an artificial neural network to estimate the probability of an ORF encoding a protein. FragGeneScan [] combines codon usage, sequence patterns for start/stop codons, […]

library_books

Sticky Genomes: Using NGS Evidence to Test Hybrid Speciation Hypotheses

2016
PLoS One
PMCID: 4871368
PMID: 27187689
DOI: 10.1371/journal.pone.0154911

[…] was an inappropriate measure of the genetic variability between the two stick insect species. Open reading frame (ORF) prediction and GC content calculation indicated a positive relationship between ORF length and GC content (). By considering sequences with a GC content of 48% or more, it was possible to exclude almost all sequences that were not dominated by predicted ORF, and thus consider a d […]

library_books

The Road to Metagenomics: From Microbiology to DNA Sequencing Technologies and Bioinformatics

2015
Front Genet
PMCID: 4681832
PMID: 26734060
DOI: 10.3389/fgene.2015.00348

[…] preferential bias in codon usage, patterns in the use of start and stop codons and, if possible, incorporates the information of species-specific ribosome-binding sites patterns, Open Reading Frame (ORF) length, and GC content of coding-sequences (Liu et al., ).To assess such tasks, some gene predictors have been designed particularly for metagenomic contig ORFs calling (Table ). For example, Met […]


Want to access the full list of citations?
LGC institution(s)
CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; Department of Biostatistics, Yale School of Public Health, New Haven, CO, USA; Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN, USA; National Center for Bioinformatics, Programme of Comparative and Evolutionary Genomics, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad, Pakistan; King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal, Saudi Arabia
LGC funding source(s)
Supported by Strategic Priority Research Program of the Chinese Academy of Sciences [XDB13040500 and XDA08020102]; National Key Research and Development Program of China [2017YFC0907502 and 2015AA020108; 2016YFE0206600]; International Partnership Program of the Chinese Academy of Sciences [153F11KYSB20160008]; National Natural Science Foundation of China [31200978]; The 100-Talent Program of Chinese Academy of Sciences; The Open Biodiversity and Health Big Data Initiative of IUBS; The 13th Five-year Informatization Plan of Chinese Academy of Sciences [XXH13505-05]; The King Abdullah University of Science and Technology (KAUST) Base Research Funds [BAS/1/1606-01-01].

LGC reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review LGC