NetSurfP 2.0 – Protein Surface Accessibility & Secondary Structure Predictions

NetSurfP 2.0

:: DESCRIPTION

NetSurfP predicts the surface accessibility and secondary structure of amino acids in an amino acid sequence. The method also simultaneously predicts the reliability for each prediction, in the form of a Z-score. The Z-score is related to the surface prediction, and not the secondary structure.

::DEVELOPER

DTU Health Tech

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

NetSurfP

:: MORE INFORMATION

Citation

A generic method for assignment of reliability scores applied to solvent accessibility predictions.
Bent Petersen, Thomas Nordahl Petersen, Pernille Andersen, Morten Nielsen and Claus Lundegaard1.
BMC Structural Biology 2009, 9:51 doi:10.1186/1472-6807-9-51.

HMMSTR 20120205 – Protein Secondary Structure Prediction

HMMSTR 20120205

:: DESCRIPTION

HMMSTR ( Hidden Markov Model for Local Sequence-Structur) is a hidden Markov model for protein structure prediction. The program takes as input an amino acid probability distribution (or profile) for each residue position. A profile may be derived from a multiple sequence alignment, or by running the database search program such as PSI_BLAST. It contains the programs needed to predict secondary structure starting with a sequence profile. The sequence profile (a vector of 20 probabilities for each residue in the sequence) can be the output of a profile HMM such as HMMer. It may also be the output of Psi-Blast, which uses profiles internally, or may be generated from a multiple sequence alignment. The programs in this package, HMMSTR and associated format converters, will give you a probabilistic prediction of each of the six DSSP symbols: H,E,G,S,T and _. For now, this is a bare-bones package.

HMMSTR Online Version

::DEVELOPER

Chris Bystroff

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Fortran compiler

:: DOWNLOAD

HMMSTR

:: MORE INFORMATION

Citaiton

BMC Bioinformatics. 2008 Oct 10;9:429. doi: 10.1186/1471-2105-9-429.
Pairwise covariance adds little to secondary structure prediction but improves the prediction of non-canonical local structure.
Bystroff C, Webb-Robertson BJ.

Bystroff C, Thorsson V & Baker D. (2000).
HMMSTR: A hidden markov model for local sequence-structure correlations in proteins.
Journal of Molecular Biology 301, 173-90.

RNAsc – RNA Secondary Structure Prediction using SHAPE or inline-probing data

RNAsc

:: DESCRIPTION

RNAsc is a web server that computes RNA secondary structure with user-input chemical/enzymatic probing data, especially Selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) or inline-probing data

::DEVELOPER

Clote Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

RNAsc

:: MORE INFORMATION

Citation:

PLoS One. 2012;7(10):e45160. doi: 10.1371/journal.pone.0045160. Epub 2012 Oct 16.
Integrating chemical footprinting data into RNA secondary structure prediction.
Zarringhalam K1, Meyer MM, Dotu I, Chuang JH, Clote P.

transFold – Super-secondary Structure Prediction of Transmembrane β-barrel proteins

transFold

:: DESCRIPTION

transFold is a web server for beta-barrel supersecondary structure prediction. Unlike other software which employ machine learning methods, transFold uses multi-tape S-attribute grammars to describe the space of all possible supersecondary structures, then applies dynamic programming to compute the global energy minimum structure.

::DEVELOPER

Clote Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

J. Waldispühl, B. Berger, P. Clote, J.-M. Steyaert,
TransFold: a Web Server for predicting the structure and residue contacts of transmembrane beta-barrels,
Nucleic Acids Res. 34(Web Server Issue):189-193 (2006).

RNAbor – Compute Structural Neighbors of an RNA Secondary Structure

RNAbor

:: DESCRIPTION

RNAbor is a web server to compute secondary structural neighbors of a given RNA structure.

::DEVELOPER

Clote Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

E. Freyhult, V. Moulton, P. Clote.
RNAbor: A web server for RNA structural neighbors.
Nucleic Acids Res. 2007 Jul 1;35(Web Server issue):W305-9. Epub 2007 May 25.

Emap2sec – Protein secondary structure detection in intermediate-resolution cryo-EM maps

Emap2sec

:: DESCRIPTION

Emap2sec is a deep learning-based tool for detecting protein secondary structures from intermediate resolution cryo-EM maps.

::DEVELOPER

Kihara Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Python

:: DOWNLOAD

Emap2sec

:: MORE INFORMATION

Citation

Nat Methods. 2019 Sep;16(9):911-917. doi: 10.1038/s41592-019-0500-1. Epub 2019 Jul 29.
Protein secondary structure detection in intermediate-resolution cryo-EM maps using deep learning.
Maddhuri Venkata Subramaniya SR, Terashi G, Kihara D.

CROSS / CROSSalign / CROSSalive – Recognition of RNA Secondary Structure

CROSS / CROSSalign / CROSSalive

:: DESCRIPTION

CROSS predicts the secondary structure propensity profile of an RNA molecule at single-nucleotide resolution. CROSS produces a table with the propensity scores and a graphical representation of the profile.

CROSSalign computes the similarity of RNA secondary structure

CROSSalive computes the structure of RNA molecules in vivo. Changes of structure upon N6-Methyladenosine methylation can be predicted.

::DEVELOPER

Tartaglia Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

CROSSalive: a web server for predicting the in vivo structure of RNA molecules.
Delli Ponti R, Armaos A, Vandelli A, Tartaglia GG.
Bioinformatics. 2019 Aug 28. pii: btz666. doi: 10.1093/bioinformatics/btz666.

Front Mol Biosci. 2018 Dec 3;5:111. doi: 10.3389/fmolb.2018.00111. eCollection 2018.
A Method for RNA Structure Prediction Shows Evidence for Structure in lncRNAs.
Delli Ponti R, Armaos A, Marti S, Tartaglia GG

A high-throughput approach to profile RNA structure.
Delli Ponti R, Marti S, Armaos A, Tartaglia GG.
Nucleic Acids Res. 2017 Mar 17;45(5):e35. doi: 10.1093/nar/gkw1094.

comRNA 1.80 – Common RNA Secondary Structure Predictor

comRNA 1.80

:: DESCRIPTION

comRNA is a new program that predicts common RNA secondary structure motifs in a group of related sequences.The algorithm applies graph-theoretical approaches to automatically detect common RNA secondary structure motifs in a group of functionally or evolutionarily related RNA sequences.

::DEVELOPER

Stormo Lab in Department of Genetics, Washington University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
GCC

:: DOWNLOAD

comRNA

:: MORE INFORMATION

Citation:

Yongmei Ji, Xing Xu and Gary D. Stormo,
A graph theoretical approach for predicting common RNA secondary structure motifs including pseudoknots in unaligned sequences, Bioinformatics, 2004 Jul 10; 20(10):1591-1602.”

AlphaPred – Prediction of Alpha-turns in Proteins using Multiple Alignment and Secondary Structure Information

AlphaPred

:: DESCRIPTION

The AlphaPred server predicts the alpha turn residues in the given protein sequence. The method is based on the neural network training on PSI-BLAST generated position specific matrices and PSIPRED predicted secondary structure.

::DEVELOPER

Dr. G P S Raghava

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Kaur H & Raghava GP. (2004).
Prediction of alpha-turns in proteins using PSI-BLAST profiles and secondary structure information.
Proteins. 55: 83-90

GammaPred – Prediction of Gamma-turns in Proteins using Multiple Alignment and Secondary Structure Information

GammaPred

:: DESCRIPTION

The GammaPred server predicts the gamma turn residues in the given protein sequence. The method is based on the neural network training on PSI-BLAST generated position specific matrices and PSIPRED predicted secondary structure. Two neural networks with a single hidden layer have been used where the first sequence-to-structure network is trained on PSI-BLAST obtained position specific matrices. The filtering has been done by second structure-to-structure network trained on output of first net and PSIPRED predicted secondary structure. The training has been carried out using error backpropagation with a sum of square error function(SSE).

::DEVELOPER

Dr. G P S Raghava

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Kaur, H. and Raghava, G.P.S. (2003)
A neural network based method for prediction of gamma-turns in proteins from multiple sequence alignment.
Protein Science 12: 923-929.