:: DESCRIPTION
MetalionRNA is a novel bioinformatic method for predicting metal-binding sites in RNA structures.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
NO
:: MORE INFORMATION
Citation
Computational methods for prediction of RNA interactions with metal ions and small organic ligands.
Philips A, Łach G, Bujnicki JM.
Methods Enzymol. 2015;553:261-85. doi: 10.1016/bs.mie.2014.10.057.
:: DESCRIPTION
MetaSSPred is a well-balanced Secondary Structure predictor
::DEVELOPER
Hoque’s Lab, University of New Orleans
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
J Theor Biol. 2015 Nov 5;389:60-71. doi: 10.1016/j.jtbi.2015.10.015. [Epub ahead of print]
A balanced secondary structure predictor.
Nasrul Islam M, Iqbal S, Katebi AR, Tamjidul Hoque M
:: DESCRIPTION
The Dragon PolyA Spotter is a tool to predict polyadenylation signals variants in primary human genomic sequences. The application displays predicted polyA signal variants and their positions in each submitted fasta sequence.
::DEVELOPER
Dragon PolyA Spotter Team @ Computational Bioscience Research Center , King Abdullah University of Science and Technology
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2012 Jan 1;28(1):127-9. Epub 2011 Nov 15.
Dragon PolyA Spotter: predictor of poly(A) motifs within human genomic DNA sequences.
Kalkatawi M, Rangkuti F, Schramm M, Jankovic BR, Kamau A, Chowdhary R, Archer JA, Bajic VB.
:: DESCRIPTION
SPEPlip is a neural network-based method, trained and tested on a set of experimentally derived signal peptides from eukaryotes and prokaryotes. SPEPlip identifies the presence of sorting signals and predicts their cleavage sites.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2003 Dec 12;19(18):2498-9.
SPEPlip: the detection of signal peptide and lipoprotein cleavage sites.
Fariselli P, Finocchiaro G, Casadio R.
:: DESCRIPTION
CCHMM_PROF is a hidden Markov model that exploits the information contained in multiple sequence alignments (profiles) to predict coiled-coil regions. The new method discriminates coiled-coil sequences with an accuracy of 97% and achieves a true positive rate of 79% with only 1% of false positives. Furthermore, when predicting the location of coiled-coil segments in protein sequences, the method reaches an accuracy of 80% at the residue level and a best per-segment and per-protein efficiency of 81% and 80%, respectively. The results indicate that CCHMM_PROF outperforms all the existing tools and can be adopted for large-scale genome annotation.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2009 Nov 1;25(21):2757-63. Epub 2009 Sep 10.
CCHMM_PROF: a HMM-based coiled-coil predictor with evolutionary information.
Bartoli L, Fariselli P, Krogh A, Casadio R.
:: DESCRIPTION
PSCOILS is a simple evolution of COILS and PCOILS programs. It uses the same parameters that were developed for COILS and exploits both sequence and evolutionary information (in the form of sequence profiles).
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
:: DESCRIPTION
The PProwler (Protein Prowler) Subcellular Localisation Predictor accepts amino acid sequences, presented in the FASTA format, and determines the localisation of the protein.
::DEVELOPER
Bioinformatics group,The University of Queensland
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
NO
:: MORE INFORMATION
Citation
Bioinformatics. 2005 May 15;21(10):2279-86. Epub 2005 Mar 3.
Prediction of subcellular localization using sequence-biased recurrent networks.
Bodén M, Hawkins J.
:: DESCRIPTION
BOMP is a tool for prediction of beta-barrel integral outer membrane proteins (BOMPs). The user may submit a list of proteins, and receive a list of predicted BOMPs.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
NO
:: MORE INFORMATION
Citation
Berven FS, Flikka K, Jensen HB, Eidhammer I.
BOMP: a program to predict integral beta-barrel outer membrane proteins encoded within genomes of Gram-negative bacteria .
Nucleic Acids Res. 2004 Jul 1;32(Web Server issue):W394-9
:: DESCRIPTION
CalPred is a “tool for EF-hand calcium binding protein prediction and calcium binding region identification” using machine learning techniques.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
:: DESCRIPTION
SNPs&GO is a server for the prediction of single point protein mutations likely to be involved in the insurgence of diseases in humans.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
No. Only Web Service
:: MORE INFORMATION
Citation
Calabrese R, Capriotti E, Fariselli P, Martelli PL, Casadio R
Functional annotations improve the predictive score of human disease-related mutations in proteins
Hum Mutat 30:1237-1244 (2009)