PESS 1.0.0 – Full-scale Protein Fold Recognition using 1NN

PESS 1.0.0

:: DESCRIPTION

PESS (Protein Empirical Structure Space) is a software of sensitive protein fold recognition using an empirical structure space and 1NN.

::DEVELOPER

the Kim Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

PESS

:: MORE INFORMATION

Citation

Middleton SA, Illuminati J, Kim J.
Complete fold annotation of the human proteome using a novel structural feature space.
Sci Rep. 2017 Apr 13;7:46321. doi: 10.1038/srep46321. PMID: 28406174; PMCID: PMC5390313.

SelfAT-Fold – Protein Fold Recognition

SelfAT-Fold

:: DESCRIPTION

selfAT-fold: protein fold recognition based on residue-based and motif-based self-attention networks

::DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

SelfAT-Fold

:: MORE INFORMATION

Citation

Pang Y, Liu B.
SelfAT-Fold: protein fold recognition based on residue-based and motif-based self-attention networks.
IEEE/ACM Trans Comput Biol Bioinform. 2020 Oct 22;PP. doi: 10.1109/TCBB.2020.3031888. Epub ahead of print. PMID: 33090951.

FoldHSphere – Deep Hyperspherical Embeddings for Protein Fold Recognition

FoldHSphere

:: DESCRIPTION

FoldHSphere is a method to learn a better fold embedding space through a two-stage training procedure.

::DEVELOPER

Amelia Villegas-Morcillo

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python
:: DOWNLOAD

FoldHSphere

:: MORE INFORMATION

Citation

Villegas-Morcillo A, Sanchez V, Gomez AM.
FoldHSphere: deep hyperspherical embeddings for protein fold recognition.
BMC Bioinformatics. 2021 Oct 12;22(1):490. doi: 10.1186/s12859-021-04419-7. PMID: 34641786; PMCID: PMC8507389.

SPPIDER – Solvent accessibility based Protein-Protein Interface iDEntification and Recognition

SPPIDER

:: DESCRIPTION

The SPPIDER protein interface recognition server can be used to: (1) predict residues to be at the putative protein interface(s) by considering single protein chain with resolved 3D structure; (2) analyse protein-protein complex with given 3D structural information and identify residues that are being in interchain contact.

::DEVELOPER

Meller Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Proteins. 2007 Feb 15;66(3):630-45.
Prediction-based fingerprints of protein-protein interactions.
Porollo A1, Meller J.

FoldRec-C2C V1 – Protein Fold Recognition by combining Cluster-to-cluster model and Protein Similarity Network

FoldRec-C2C V1

:: DESCRIPTION

FoldRec-C2C is a predictor to globally incorporate the interactions among proteins into the prediction.

::DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

FoldRec-C2C

:: MORE INFORMATION

Citation

Shao J, Yan K, Liu B.
FoldRec-C2C: protein fold recognition by combining cluster-to-cluster model and protein similarity network.
Brief Bioinform. 2021 May 20;22(3):bbaa144. doi: 10.1093/bib/bbaa144. PMID: 32685972; PMCID: PMC7454262.

SProtP – Recognition of Short-lived Human Proteins

SProtP

:: DESCRIPTION

SProtP is a web server of recognition of short-lived proteins based on sequence-derived features in human cells

::DEVELOPER

SProtP team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

PLoS One. 2011;6(11):e27836. doi: 10.1371/journal.pone.0027836. Epub 2011 Nov 16.
SProtP: a web server to recognize those short-lived proteins based on sequence-derived features in human cells.
Song X1, Zhou T, Jia H, Guo X, Zhang X, Han P, Sha J.

miREE – miRNA Recognition Elements Ensemble

miREE

:: DESCRIPTION

miREE is a novel microRNA target prediction tool consisting of two parts entailing complementary but integrated roles in the prediction.

::DEVELOPER

EDA (Electronic Design Automation Group)

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

miREE: miRNA recognition elements ensemble.
Reyes-Herrera PH, Ficarra E, Acquaviva A, Macii E.
BMC Bioinformatics. 2011 Nov 24;12:454. doi: 10.1186/1471-2105-12-454.

PredictFold-PSS-3D1D – Protein Fold Recognition Web Server

PredictFold-PSS-3D1D

:: DESCRIPTION

The PredictFold PSS-3D1D is a fold recognition server based on Protein Secondary Structure and 3D1D Profiles.

::DEVELOPER

Research Group of Dr.S.Parthasarathy

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Ganesan K & Parthasarathy S (2013)
PredictFold-PSS-3D1D: A Protein Fold Recognition Server for Predicting Folds from the Twilight Zone Sequences.
Current Bioinformatics. 8(5):552-556.

J Struct Funct Genomics. 2011 Dec;12(4):181-9. doi: 10.1007/s10969-011-9119-x. Epub 2011 Dec 3.
PSS-3D1D: an improved 3D1D profile method of protein fold recognition for the annotation of twilight zone sequences.
Ganesan K1, Parthasarathy S.

RCADE 1.0 – Recognition Code-Assisted Discovery of Regulatory Elements

RCADE 1.0

:: DESCRIPTION

RCADE combines predictions from a DNA recognition code of C2H2-ZFs with ChIP-seq data to identify models that represent the genuine DNA binding prefer-ences of C2H2-ZF proteins.

::DEVELOPER

Hamed S. Najafabadi at the Hughes lab in the Terrence Donnelly Centre for Cellular and Biomolecular Research

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • R

:: DOWNLOAD

 RCADE

:: MORE INFORMATION

Citation

Identification of C2H2-ZF binding preferences from ChIP-seq data using RCADE.
Najafabadi HS, Albu M, Hughes TR.
Bioinformatics. 2015 May 6. pii: btv284

ORION – Profile-profile Fold Recognition

ORION

:: DESCRIPTION

ORION (Optimized fold RecognitION) is a new fold recognition method based on the pairwise comparison of hybrid profiles that contain evolutionary information from both protein sequence and structure.

::DEVELOPER

the DSIMB bioinformatic group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 ORION

:: MORE INFORMATION

Citation

Improving protein fold recognition with hybrid profiles combining sequence and structure evolution.
Ghouzam Y, Postic G, de Brevern AG, Gelly JC.
Bioinformatics. 2015 Aug 7. pii: btv462.

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