SEED functionally, and furthermore protein families derived from them.

SEED is used by many researchers for predicting gene
function and discovering new pathways. SEED also has a collection of protein
families that are related functionally, and furthermore protein families
derived from them. The core of RAST annotation system is the interconnection of
RAST and SEED. The SEED continuously integrates different types of genomic data
from a variety of sources. These include public genomes annotated by RAST,
expert user annotation, metabolic modeling data, expression data, literature
references verifying annotations and links to data from popular resources
including Swissport, Genbank, IMG. KEGG, CDD and so forth. The SEED website
works like a google search engine for genome annotation and comparison. SEED
and RAST are a big tool to understand genome because these programs have
multiple genome analysis tools. RAST is an annotation system built on the
framework provided by SEED. RAST can also identify protein coding regions,
tRNA, rRNA, non-coding RNA, etc. Overall the article gives a detailed information
on RAST and SEED relationship and how future developments of RAST can make it
even more easier for researchers to annotate genome using wide variety of
tools.

 

Mauve is a great tool when there is a need to construct
multiple genome alignments in the presence of rearrangement ir inversion. Since
mutations will occur with the course of evolution of which some are large scale
mutations (include gain or loss of large segments generated by unequal
recombination) or Local mutations (nucleotide substitution, insertion, deletion).  With the help of Mauve, it is possible to
examine what has changed in a mutant genome sequence as compared to parent genome
sequence. Progressive Mauve generates positional homology multiple genome
alignments. Mauve doesn’t require the user to use complex algorithms, instead
it is very user friendly. The time frame in which an alignment is completed, depends
on job load.

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Resfinder is a web based system that depends on BLAST for
identification of acquired antimicrobial resistant genes in whole genomic data.

The article mentions that 1862 genbank files were tested. The goal was to
identify and study the antimicrobial resistant genes. As researcher’s research,
more and more genes on this platform, the database accumulates the information
and grows with every entry. To experiment, Resfinder was used on twenty-three
isolates of five different bacterial species and on WSG chromosomes and
plasmids of 30 isolates. A few of these isolates were annotated by the system,
to have a microbial resistance. Overall resfinder is an easy and free resource
that can help identify the antimicrobial resistant genes.

 

Phylosift is a method to analyze metagenomics samples from
phylogenetic viewpoint of community structure among multiple related samples. The
analysis can be broken down into four stages. In the first stage the query is searched
for in the reference gene families. Then the second step is that input
sequences are added to a multiples alignment sequence with reference genes. The
third step is that the input sequences is placed on a phylogeny of reference genes.

The fourth and the last step is the generation of taxonomic summaries. The standard
phylosift database has 37 “Elite” gene families identified as universal and
present in a single copy. In addition, phylosift database also includes four
additional sets of gene families: 16s and 18s ribosomal RNA genes, mitochondrial
gene families, viral gene families. In total 800 gene families exist of which
most are viral. Phylosift provides several advantages over OUT-based or taxonomic
analysis for metagenomics data. Phylosift model reduces errors because it
relies on evolutionary models to correctly align unknown sequences within a
known topology. Phylosift can also prevent errors in microbial forensics. With
all these great functions, phylosift proves to be a great tool for research in
metagenomics.