Address of the bookmark: http://kobas.cbi.pku.edu.cn/

tax_id:
the unique identifier provided by NCBI Taxonomy
for the species or strain/isolate

GeneID:
the unique identifier for a gene
ASN1: geneid

Symbol:
the default symbol for the gene
ASN1: gene->locus

LocusTag:
the LocusTag value
ASN1: gene->locus-tag

Synonyms:
bar-delimited set of unofficial symbols for the gene

dbXrefs:
bar-delimited set of identifiers in other databases
for this gene. The unit of the set is database:value.
Note that HGNC and MGI include 'HGNC' and 'MGI', respectively,
in the value part of their identifier. Consequently,
dbXrefs for these databases will appear like:
HGNC:HGNC:1100
This would be interpreted as database='HGNC', value='HGNC:1100'
Example for MGI:
MGI:MGI:104537
This would be interpreted as database='MGI', value='MGI:104537'

chromosome:
the chromosome on which this gene is placed.
for mitochondrial genomes, the value 'MT' is used.

map location:
the map location for this gene

description:
a descriptive name for this gene

type of gene:
the type assigned to the gene according to the list of options
provided in https://www.ncbi.nlm.nih.gov/IEB/ToolBox/CPP_DOC/lxr/source/src/objects/entrezgene/entrezgene.asn

Symbol from nomenclature authority:
when not '-', indicates that this symbol is from a
a nomenclature authority

Full name from nomenclature authority:
when not '-', indicates that this full name is from a
a nomenclature authority

Nomenclature status:
when not '-', indicates the status of the name from the
nomenclature authority (O for official, I for interim)

Other designations:
pipe-delimited set of some alternate descriptions that
have been assigned to a GeneID
'-' indicates none is being reported.

Modification date:
the last date a gene record was updated, in YYYYMMDD format

Feature type:
pipe-delimited set of annotated features and their classes or
controlled vocabularies, displayed as feature_type:feature_class
or feature_type:controlled_vocabulary, when appropriate; derived
from select feature annotations on RefSeq(s) associated with the
GeneID

Address of the bookmark: ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/

Address of the bookmark: https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0082

https://academic.oup.com/nar/article/47/11/e63/5377471

Address of the bookmark: https://github.com/linzhi2013/MitoZ

Address of the bookmark: http://schatzlab.cshl.edu/data/nanocorr/

" the microbes exist in very low concentrations, of around 1,000 microbes in every tea spoon full of rock, compared with billions or trillions of bacteria that would typically be found in the same amount of soil at Earth's surface."

Reference:

http://www.bbc.co.uk/news/science-environment-23855436

GTDB-Tk is under active development and validation. Please independently confirm the GTDB-Tk predictions by manually inspecting the tree and bringing any discrepencies to our attention. Notifications about GTDB-Tk releases will be available through the ACE Twitter account (https://twitter.com/ace_uq).

Address of the bookmark: https://github.com/Ecogenomics/GTDBTk

Specifically, the taxonomy() function implemented in myTAI can be used to classify genomes according to phylogenetic classification into Phylostrata (Phylostratigraphy) or to retrieve species specific taxonomic information when performing Divergence Stratigraphy (see Introduction for details).

Address of the bookmark: https://cran.r-project.org/web/packages/myTAI/vignettes/Taxonomy.html

The GO provides core biological knowledge representation for modern biologists, whether computationally or experimentally based. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Although extensively used in data analysis workflows, and widely incorporated into numerous data analysis platforms and applications, the general user of GO resources often misses fundamental distinctions about GO structures, GO annotations, and what can and can not be extrapolated from GO resources. Here are ten quick tips for using the Gene Ontology.

Read "Ten Quick Tips for Using the Gene Ontology" at http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1003343

Following are the most commonly used old and new GO term enrichment determination tools. These tools are recommended to people working in a wet-lab.

CLASSIFI (Department of Pathology, UT Southwestern Medical Center)

CLASSIFI (Cluster Assignment for Biological Inference) is a data-mining tool that can be used to identify significant co-clustering of genes with similar functional properties (e.g. cellular response to DNA damage). Briefly, CLASSIFI uses the Gene OntologyTM (GO) gene annotation scheme to define the functional properties of all genes/probes in a microarray data set, and then applies a cumulative hypergeometric distribution analysis to determine if any statistically significant gene ontology co-clustering has occurred.

http://pathcuric1.swmed.edu/pathdb/classifi.html

EasyGO (China Agricultural University)

EasyGO is designed to automate enrichment job for experimental biologists to identify enriched Gene Ontology (GO) terms in a list of microarray probe sets or gene identifiers (with expression information for PAGE analysis). Also EasyGO is also a GO annotation database, especially focus on agronomical species, supporting 30 species. It is user friendly, with advanced result browsing format and in-time update.

http://bioinformatics.cau.edu.cn/neweasygo/

http://bioinformatics.cau.edu.cn/easygo/

g:GOSt (Institute of Computer Science, University of Tartu)

g:GOSt retrieves most significant Gene Ontology (GO) terms, KEGG and REACTOME pathways, and TRANSFAC motifs to a user-specified group of genes, proteins or microarray probes. g:GOSt also allows analysis of ranked or ordered lists of genes, visual browsing of GO graph structure, interactive visualisation of retrieved results, and many other features. Multiple testing corrections are applied to extract only statistically important results.

http://biit.cs.ut.ee/gprofiler/

DAVID : Gene Functional Classification (Laboratory of Immunopathogenesis and Bioinformatics, NIAID)

The Functional Classification Tool provides a rapid means to organize large lists of genes into functionally related groups to help unravel the biological content captured by high throughput technologies.

http://david.abcc.ncifcrf.gov/gene2gene.jsp

http://david.abcc.ncifcrf.gov/

API https://github.com/chrisamiller/davidapi

GOEAST (Institute of Genetics and Developmental Biology, Chinese Academy of Sciences)

GOEAST is web based software toolkit providing easy to use, visualizable, comprehensive and unbiased Gene Ontology (GO) analysis for high-throughput experimental results, especially for results from microarray hybridization experiments. The main function of GOEAST is to identify significantly enriched GO terms among give lists of genes using accurate statistical methods.

http://omicslab.genetics.ac.cn/GOEAST/

GOstat (Walter and Eliza Hall Institute of Medical Research)

Find statistically overrepresented GO terms within a group of genes

http://gostat.wehi.edu.au/

GOrilla (Technion - Laboratory of Computational Biology , Israel Institute of Technology)

GOrilla is a tool for identifying and visualizing enriched GO terms in ranked lists of genes.
It uses two approaches, first by searching for enriched GO terms that appear densely at the top of a ranked list of genes  or by searching for enriched GO terms in a target list of genes compared to a background list of genes.

GOrilla makes nice pictures !!!!

http://cbl-gorilla.cs.technion.ac.il/

Gene Ontology for Functional Analysis (GOFFA)

GOFFA is a tool developed for ArrayTrack™ that takes a list of genes and identifies terms in Gene Ontology (GO) disclaimer icon associated with those genes.

It provides several tools to view/access the GO term hierarchy, full listing of GO terms annotated with the genes associated with a given term with statically useful report.

http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm233315.htm

GOAT (The University of Manchester)

The aim of the GOAT project is to create an application that will guide users, especially biomedical researchers, in the annotation of gene products with terms from the Gene Ontology.

http://goat.man.ac.uk/

Script https://github.com/tanghaibao/goatools/

REVIGO ( Rudjer Boskovic Institute, Croatia)

REViGO is a web server that can take long lists of Gene Ontology terms and summarize them by removing redundant GO terms. The remaining terms can be visualized in semantic similarity-based scatterplots, interactive graphs, or tag clouds.

http://revigo.irb.hr/

QuickGo (EMBL-EBI Institute)

It uses extensive computational filters to allow the generation of specific subsets of GO annotations, mapped to sequence identifiers of your choice. Then GO slims are used which is collective list of GO full set of terms available from the Gene Ontology project.

http://www.ebi.ac.uk/QuickGO/

GOLEM

An interactive graph-based gene-ontology navigation and analysis tool. GOLEM is a userful tool which allows the viewer to navigate and explore a local portion of the Gene Ontology (GO) hierarchy.

http://reducio.princeton.edu/GOLEM/

BGI Web Gene Ontology (WEGO) Annotation Plot (Beijing Genomics Institute)

WEGO () is a useful tool for plotting GO annotation results. It has been widely used in many important biological research projects, such as the rice genome project [Yu, J. et al. Science 296, 79-92 (2002); Yu, J. et al. PLoS Biol 3, e38 (2005)] and the silkworm genome project [Xia, Q. et al. Science 306, 1937-40 (2004)]. It has become one of the daily tools for downstream gene annotation analysis, especially when performing comparative genomics tasks. WEGO along with two other tools, namely External to GO Query and GO Archive Query, are freely available for all users. Any suggestions are welcome at wego@genomics.org.cn. Here is a sample output generated by WEGO

http://wego.genomics.org.cn/cgi-bin/wego/index.pl

GeneGO MetaCore (MIT)

GeneGo is a leading provider of data mining & analysis solutions in systems biology. MetaCore, GeneGo's flapship product, is an integrated software suite for functional analysis of experimental data. MetaCore is based on a curated database of human protein-protein, protein-DNA interactions, transcription factors, signaling and metabolic pathways, disease and toxicity, and the effects of bioactive molecules.

https://portal.genego.com/

GOEx (Stony Brook University)

GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics.

http://pcarvalho.com/patternlab

GOssTo

GOssTo and GOssToWeb are tools to calculate the semantic similarity between genes or terms in the Gene Ontology.

http://www.paccanarolab.org/gosstoweb/

GO Workbench

The Gene Ontology Analysis Viewer allows direct browsing of the Gene Ontology, and also the visualization of GO Term analysis results.

http://wiki.c2b2.columbia.edu/workbench/index.php/Gene_Ontology_Viewer

Some other useful list of GO software and tools is available at http://www.geneontology.org/GO.tools.shtml#browser

Yet another useful webpage with list of GO tools at http://neurolex.org/wiki/Category:Resource:Gene_Ontology_Tools

It was first developed to transfer annotations between different genome assembly versions. However, it can also transfer annotations between strains and even different species, like Plasmodium chabaudi onto P. berghei, between different Leishmania species or Salmonella enterica onto other Salmonella serotypes. RATT is able to transfer any entries present on a reference sequence, such as the systematic id or an annotator's notes; such information would be lost in a de novo annotation.

More at http://ratt.sourceforge.net/

Address of the bookmark: http://ratt.sourceforge.net/