MemType-2L – Predicting Membrane Protein Types

MemType-2L

:: DESCRIPTION

MemType-2L is a 2-layer predictor for predicting membrane protein types, the first layer will predict whether the query sequence belongs to membrane proteins or not; and the second layer aims to predict exactly the membrane protein types when the output of the first layer is “membrane proteins”.

::DEVELOPER

Computational Systems Biology Group, Shanghai Jiao Tong University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

Biochem Biophys Res Commun. 2007 Aug 24;360(2):339-45. Epub 2007 Jun 15.
MemType-2L: a web server for predicting membrane proteins and their types by incorporating evolution information through Pse-PSSM.
Chou KC1, Shen HB.

memembed 1.15 – Membrane Protein Orientation Predictor

memembed 1.15

:: DESCRIPTION

memembed is a software of membrane protein orientation and refinement using a knowledge-based statistical potential

::DEVELOPER

Bioinformatics Group – University College London

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 memembed

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2013 Sep 18;14:276. doi: 10.1186/1471-2105-14-276.
Membrane protein orientation and refinement using a knowledge-based statistical potential.
Nugent T1, Jones DT.

MERMAID – Prepare and Run Coarse-Grained Membrane Protein Dynamics

MERMAID

:: DESCRIPTION

MERMAID (Martini coarsE gRained MembrAne proteIn Dynamics) is a publicly available web interface that allows the user to prepare and run coarse-grained molecular dynamics (CGMD) simulations and to analyse the trajectories

::DEVELOPER

Applied Bioinformatics Group, University of Verona

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Nucleic Acids Res, 47 (W1), W456-W461 2019 Jul 2
MERMAID: Dedicated Web Server to Prepare and Run Coarse-Grained Membrane Protein Dynamics
Mangesh Damre , Alessandro Marchetto , Alejandro Giorgetti

MEDELLER – Homology-Based Coordinate Generation for Membrane Proteins

MEDELLER

:: DESCRIPTION

MEDELLER, a MP(Membrane proteins)-specific homology-based coordinate generation method,  which is optimized to build highly reliable core models.

::DEVELOPER

the Oxford Protein Informatics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Nov 15;26(22):2833-40. doi: 10.1093/bioinformatics/btq554. Epub 2010 Oct 5.
MEDELLER: homology-based coordinate generation for membrane proteins.
Kelm S, Shi J, Deane CM.

MP-T 201407 – Membrane Protein Sequence-structure Alignment

MP-T 201407

:: DESCRIPTION

MP-T is a sequence-structure alignment algorithm for membrane proteins. It produces accurate sequence alignments for use in homology modelling. The inputs are a fasta-formatted sequence and an annotated structure file from the iMembrane webserver.

::DEVELOPER

Oxford Protein Informatics Group (OPIG)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

  MP-T

:: MORE INFORMATION

Citation

Jamie R. Hill and Charlotte M. Deane
MP-T: improving membrane protein alignment for structure prediction
Bioinformatics (2013) 29 (1): 54-61.

Memoir – Membrane Protein Modelling Pipeline

Memoir

:: DESCRIPTION

Memoir (MEMbrane prOteIn modelleR) is a homology modelling algorithm designed for membrane proteins. The inputs are the sequence which is to be modelled, and the 3D structure of a template membrane protein.

::DEVELOPER

Oxford Protein Informatics Group (OPIG)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2013 Jul;41(Web Server issue):W379-83. doi: 10.1093/nar/gkt331. Epub 2013 May 2.
Memoir: template-based structure prediction for membrane proteins.
Ebejer JP1, Hill JR, Kelm S, Shi J, Deane CM.

MycoMemSVM – Identification of Mycobacterial Membrane Proteins

MycoMemSVM

:: DESCRIPTION

MycoMemSVM is a sequence-based predictor for identifying mycobacterial membrane proteins and their types

::DEVELOPER

LinDing Group

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

J Proteomics. 2012 Dec 21;77:321-8. doi: 10.1016/j.jprot.2012.09.006. Epub 2012 Sep 20.
Identification of mycobacterial membrane proteins and their types using over-represented tripeptide compositions.
Ding C1, Yuan LF, Guo SH, Lin H, Chen W.

Mem-mEN – Interpretable Membrane Protein Type Prediction

Mem-mEN

:: DESCRIPTION

Mem-mEN leverages a multi-label elastic net (EN) classifier, which can yield sparse and interpretable solutions for large-scale prediction of membrane proteins with single- and multi-label functional types.

::DEVELOPER

Dr. Man-Wai Mak

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

IEEE/ACM Trans Comput Biol Bioinform. 2015 Aug 28.
Mem-mEN: Predicting Multi-Functional Types of Membrane Proteins by Interpretable Elastic Nets.
Wan S, Mak MW, Kung SY.

Mem-ADSVM – Multi-Label Membrane Protein Type Prediction

Mem-ADSVM

:: DESCRIPTION

Mem-ADSVM is a two-layer multi-label membrane-protein functional-type predictor, which can identify membrane proteins (Layer I) and their multi-functional types (Layer II).

::DEVELOPER

Dr. Man-Wai Mak

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Mem-ADSVM: A Two-Layer Multi-Label Predictor for Identifying Multi-Functional Types of Membrane Proteins.
Wan S, Mak MW, Kung SY.
J Theor Biol. 2016 Mar 18. pii: S0022-5193(16)00154-5. doi: 10.1016/j.jtbi.2016.03.013.

iMem-Seq – Predicting Membrane Proteins Types

iMem-Seq

:: DESCRIPTION

iMem-Seq is a multi-label classifier for identifying membrane proteins with single and multiple types via physical-chemical property matrix and grey-PSSM

::DEVELOPER

JCI BioInfo Lab

:: SCREENSHOTS

n/a

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

J Membr Biol. 2015 Aug;248(4):745-52. doi: 10.1007/s00232-015-9787-8. Epub 2015 Mar 22.
iMem-Seq: A Multi-label Learning Classifier for Predicting Membrane Proteins Types.
Xiao X1, Zou HL, Lin WZ.