Webserver
Genome annotation
Structure prediction
Functional annotation
vaccine design
Databases
Miscellaneous
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Server
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Description
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APSSP2
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This server predicts secondary
structure of protein's from their amino acid sequence with high accuracy. It
uses the multiple alignment, neural network and MBR techniques. This server
participates in number of world wide competition like CASP, CAFASP and EVA (Raghava
2002; CASP5 A-31)
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PROCLASS
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Prediction of structural class
of proteins such as Alpha or Beta or Alpha+Beta or Alpha/Beta (Raghava
1999; J. Biosciences 24:176)
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PSA
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This server allow user to
analysis of protein sequence and present the analysis in Graphical and
Textual format. This allows property plots of 36 parameter (like
Hydrophobicity Plot, Polarity, Charge) of single sequence and multiple
sequence alignment (Raghava 2001; Biotech Software and Internet Report,
2:255)
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RPFOLD:
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It allows to predict top 5
similar fold in PDB (Protein DataBank) for a given protein sequence (query)
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BTeval:
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Benchmarking of Beta Turn
prediction methods on-line via Internet (Kaur and Raghava 2002;
Bioinformatics 18:1508-14). The user can see the performance of their
method or existing methods (Kaur and Raghava 2003; Journal of
Bioinformatics and Computational Biology 1:495-504)
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BetatTPred2:
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Prediction of Beta Turns in
Proteins using Neural Network and multiple alignment techniques. This is
highly accurate method for beta turn prediction (Kaur and Raghava 2003;
Protein Science 12:627).
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GammaPred:
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Prediction of Gamma-turns in
Proteins using Multiple Alignment and Secondary Structure Information (Kaur
and Raghava 2003; Protein Science; 12:923).
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AlphaPred:
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Prediction of Alpha-turns in
Proteins using Multiple Alignment and Secondary Structure Information (Kaur
& Raghava 2004; Proteins 55:83-90).
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BetaTPred:
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A server for predicting Beta
Turns in proteins using existing statistical methods. This allows consensus
prediction from various methods (Kaur and Raghava 2002; Bioinformatics 18:498)
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CHpredict:
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The CHpredict server predict
two types of interactions: C-H...O and C-H...PI interactions. For C-H...O
interaction, the server predicts the residues whose backbone Calpha atoms are
involved in interaction with backbone oxygen atoms and for C-H...PI
interactions, it predicts the residues whose backbone Calpha atoms are
involved in interaction with PI ring system of side chain aromatic moieties.
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AR_NHPred:
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A web server for predicting the
aromatic backbone NH interaction in a given amino acid sequence where the pi
ring of aromatic residues interact with the backbone NH groups. The method is
based on the neural network training on PSI-BLAST generated position specific
matrices and PSIPRED predicted secondary structure (Kaur and Raghava 2004; Febs Lett. 564:47-57)
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TBBpred:
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It predicts the whether a
protein is outer membrane betat-barrel protein or not. It also predicts
transmembrane Beta barrel regions in a given protein sequence. (Natt et al. 2004; Proteins 56:11-8).
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Betaturns:
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This server predicts the beta
turns and their types in a protein from its amino acid sequence (Kaur and
Raghava 2004; Bioinformatics 20:2751-8) .
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PEPstr:
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The Pepstr server predicts the
tertiary structure of small peptides with sequence length varying between 7
to 25 residues. The prediction strategy is based on the realization that
?-turn is an important and consistent feature of small peptides in addition
to regular structures.
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BhairPred:
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Prediction of beta hairpins in
proteins using ANN and SVM techniques. In this method secondary structure and
multiple sequence alignment are used
to predict the beta hairpins (Kumar et al. 2005; Nucleic Acids Res.
33:W154-9)
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SARpred:
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Prediction of real value of
surface accessibility instead of buried or exposed residues in proteins from
amino acid sequence (Garg et al. 2005; Proteins,
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OXbench:
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A
bench-mark for evaluation of protein multiple sequence alignment accuracy (Raghava
et al. 2003; BMC Bioinformatics 4-47).
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Server
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Description
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ProPred1:
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The
aim of this server is to predict MHC Class-I binding regions in an antigen
sequence (Singh, H. and Raghava, G.P.S. (2003) Bioinformatics, 19: 1009)
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ProPred:
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The
aim of this server is to predict MHC Class-II binding regions in an antigen
sequence (Singh, H. and Raghava, G. P. S. (2001) Bioinformatics 17: 1236)
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BcePred:
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The
BcePred server predict B cell epitope based on physio-chemical properties of
amino acids. (Saha,S and Raghava GP (2004) ICARIS, LNCS 3239,197-204)
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nHLAPred:
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This
server allow to predict binding peptide for 67 MHC Class I alleles. This also
allow to predict the proteasome cleavage site and binding peptide that have
cleavage site at C terminus (potential T cell epitopes). This uses the hybrid
approach for prediction (Neural Network + Quantitative Matrix)
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HLADR4Pred:
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SVM
and ANN based methods for predicting HLA-DRB1*0401 binding peptides in an
Antigen Sequence (Bhasin, M. and Raghava, G.P.S. (2003) Bioinformatics
20:421).
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ABCpred:
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ABCpred
server is to predict linear B cell epitope regions in an antigen sequence, using
artificial neural network. This server will assist in locating epitope
regions that are useful in selecting synthetic vaccine candidates, disease
diagonosis and also in allergy research.
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MMBPred
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Prediction
of of MHC class I binders which can bind to wide range of MHC alleles with
high affinity. This server has potential to develop sub-unit vaccine for
large population (Bhasin, M., and Raghava, G.P.S. (2003) Hybridoma and
Hybridomics 22: 229)
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MHC2Pred:
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Prediction
of binders for MHC class II alleles. This allows to predict promiscuous class binders, which can bind
to large number of MHC Class II alleles.
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Bcipep:
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Bcipep
is a collection of the peptides having the role in Humoral immunity. The
peptides in the database has varying measure of immunogenicity.This database can
assist in the development of method for predicting B cell epitopes,
desigining synthetic vaccines and in disease diagnosis. This databse is also
launched by European Bioinformatics Institute (EBI) Hinxton, Cambridge, UK. (Saha S, Bhasin M, Raghava GP. (2005) BMC Genomics. 6(1):79)
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Pcleavage:
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This
server allows server to predict
proten (Immuno and standard) (Bhasin M, Raghava GP. (2005) Nucleic Acids Res.33(Web Server
issue):W202-7)
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MHC
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Matrix Optimization Technique for Predicting
MHC binding Core (Singh, H. and Raghava, G. P. S. (2002) Biotech Software
and Internet Report, 3:146)
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HLAPRED:
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A
server for predicting binders for MHC class I and II alleles. It also search
these predicted binders in various genomes.
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TAPPred:
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TAPPred
is an on-line service for predicting binding affinity of peptides toward the
TAP transporter. The Prediction is based on cascade SVM, using sequence and
properties of the the amino acids (Bhasin, M. and Raghava, G. P. S. (2004)
Protein Science 13:596-607).
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MHCBench :
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It is an interface developed for evaluating the Major
Histocompatibility Complex (MHC) binding peptide prediction algorithms.
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MHCBN:
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The
MHCBN is a curated database consisting of detailed information about Major
Histocompatibility Complex (MHC) Binding,Non-binding peptides and T-cell
epitopes.The version 3.1 of database provides information about peptides interacting
with TAP and MHC linked autoimmune diseases This databse is also launched by
European Bioinformatics Institute (EBI) Hinxton, Cambridge, UK. (Bhasin,
M., Singh, H. and Raghava, G. P. S. (2003) Bioinformatics 19: 665).
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CTLPred:
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Direct
method of prediction of CTL Epitopes in an antigen sequence. This server
utlize the machine learning techniques Support Vector Machine(SVM) and
Aritificial Neural Network (ANN) for prediction (Bhasin, M. and Raghava,
G. P. S. (2004) Vaccine 22:3195-204
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Ab/Ag concentartion
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This
web-server allow to compute the endpoint titer and concentration of
Antibody(Ab) or Antigen(Ag) from ELISA data(Raghava, G. P. S. and Agrewala,
J. N. (2001) Biotech Software and Internet Report, 2:196). This server is
based on graphical method developed for calculating Ab/Ag concentration (Raghava,
G.P.S., Joshi, A.K. and Agrewala, J.N. (1992) J. Immunol. Methods 153,
263-264).
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HaptenDB:
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A
database of hapten molecules which
can not activate immune system but can stimulate immune response if attach
with the carrier proteins.
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Server
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Description
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AC2DGel:
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This is a web server for analysis and
comparison of two-dimensional electrophoresis (2-DE) Gel images. It helps in
annotating the virual 2-D gel image proteins on the basis of known molecular
weight andpH scales of the markers.
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ESLpred:
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This
is a SVM based method for predicting subcellular localization of Eukaryotic
proteins using dipeptide composition and PSIBLAST generated pfofile Using
this server user may know the function of their protein based on its location
in cell. (Bhasin, M. and Raghava, G. P. S., (2004) Nucleic Acid Res. 32(Web Server issue):W414-9).
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NRpred:
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This
is a SVM based tool for the classification of nuclear receptors on the basis
of amino acid composition or dipeptide composition. The overall prediction
accuracy of amino acid composition and dipeptide composition based methods is
82.6% and 97.2% (Bhasin, M. and Raghava, G. P. S., (2004) Journal of
Biological Chemistry 279(22):23262-6)
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GPCRpred:
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This is a server forpredicting
G-protein-coupled receptors and for classifying them in families and
sub-families. This server can play vital role in drug design, as GPCR are
commonly used as drug targets (Bhasin, M. and Raghava, G. P. S., (2004)
Nucleic Acid Res. 32(Web
Server issue):W383-9)
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GPCRSclass:
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This is a dipeptide composition based method
for predicting Amine Type of G-protein-coupled receptors. In this method type
amine is predicted from dipeptide composition of proteins using SVM. (Bhasin M, Raghava GP. (2005) 33(Web Server
issue):W143-7)
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Comp2DGel:
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Comparison,
management and access of 2D gel electrophoresis
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DNASIZE
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This web-server allow to compute the length of
DNA or protein fragments from its electropheric mobility using a graphical
method (Raghava, G. P. S. (2001) Biotech Software and Internet Report,
2:198).
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HSLpred:
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This server allows predicting the subcellulare
localization of human proteins. This is based on various type of residue
composition of proteins using SVM technique. (Garg A, Bhasin M, Raghava GP. J Biol Chem.
(2005) 280(15):14427-32)
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PSLpred:
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A
method for subcellular localization proteins belongs to prokaryotic genomes.
The pathogen play an important role in our life.
(Bhasin M, Garg A, Raghava
GP. Bioinformatics. (2005) 21(10):2522-4)
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MANGO:
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Prediction of manually annotated proteins in
Genome Ontology (GO). This server is based on nearest neighbor
method (NNM).
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Btxpred
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The
aim of BTXpred server is to predict bacterial toxins and its function
from primary amino acid sequence.
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Mitpred
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This
server predicts mitochondril proteins
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SRTpred
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This
server classifies protein sequence as secretory or non-secretory proteins
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Hemopred
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It
allows users to predict hemoglobin protein
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VGIchan
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The
aim of this server is to predict voltage gated ion-channels and classify them
into sodium, potassium, calcium and chloride ion channels from primary amino
sequences.
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SGpred
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This
server allows user to identify and visulaze the genes which have different
expression level in normal and disease conditions.
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LGEpred
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This
server allows user to analsis the expresion data (Microarray Data) where it
calculate correlation coefficient between amino acid residue and gene
expression level.
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NTXpred
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The
aim of this server is to predict neurotoxins and it source and probable
functions from primary amino acid sequences
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VICMpred
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This
server aids in broad functional classification of bacterial proteins into
virulence factors, information molecule, cellular process and metabolism molecule.
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Server
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Description
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FTG:
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A web server for locating probable
protein coding region in nucleotide sequence using fourier tranform approach (Issac,
B., Singh, H., Kaur, H. and Raghava, G.P.S. (2002) Bioinformatics 18:196).
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EGPred
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This server allows to predict gene (protein coding
regions) in eukaryote genomes that includes introns and exons, using similarity
aided (double) and consensus Ab Intion methods. (Issac B, Raghava GP. (2004) Genome Res.
14(9):1756-66)
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FTGPred:
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A web server for predicting
genes in a DNAsequence
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GWBLAST:
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A genome wide blast server. It allow
user to search ther sequence against sequenced genomes and annonated
proteomes. This integrate various tools which allows analysys of BLAST SEARCH
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SVMgene:
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It is a support vector based approach to identify the
protein coding regions in human genomic DNA
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SRF:
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Spectral Repeat Finder (SRF) is a
program to find repeats through an analysis of the power spectrum of a given
DNA sequence. By repeat we mean the repeated occurrence of a segment of N
nucleotides within a DNA sequence. SRF is an ab initio technique as no prior
assumptions need to be made regarding either the repeat length, its fidelity,
or whether the repeats are in tandem or not (Sharma D, Issac B, Raghava GP, Ramaswamy R. (2004) Bioinformatics.
20(9):1405-12)
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GWFASTA:
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Genome Wise Sequence Similarity Search
using FASTA. It allow user to search their sequence against sequenced genomes
and their product proteome. This integrate various tools which allows
analysys of FASTA search (Issac, B. and Raghava, G.P.S. (2002)
Biotechniques 33:548-56).
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GeneBench:
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A suite of datasets and tools for
evaluating gene prediction methods.
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MyPattern
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MyPattern Finder is a program for detection of a 'motif'
in DNA sequence by using an exact search method (Option A (1.0))
or an alignment technique (Option B
(1.0)).
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