SABINE 1.2 – Prediction of the Binding Specificity of Transcription Factors using Support Vector Regression

SABINE 1.2

:: DESCRIPTION

SABINE (Stand-alone binding specificity estimator) is a tool to predict the binding specificity of a transcription factor (TF), given its amino acid sequence, species, structural superclass and DNA-binding domains. For convenience, the superclass and DNA-binding domains of a given TF can be predicted based on sequence homology with TFs in the training of SABINE.

::DEVELOPER

the Center for Bioinformatics Tübingen (Zentrum für Bioinformatik Tübingen, ZBIT).

:: SCREENSHOTS

:: REQUIREMENTS

Linux
Java

:: DOWNLOAD

SABINE

:: MORE INFORMATION

Citation

PLoS One. 2013 Dec 12;8(12):e82238. doi: 10.1371/journal.pone.0082238. eCollection 2013.
TFpredict and SABINE: Sequence-Based Prediction of Structural and Functional Characteristics of Transcription Factors.
Eichner J, Topf F1, Dräger A, Wrzodek C, Wanke D, Zell A.

BERT-Kcr – Prediction of Protein Lysine Crotonylation sites

BERT-Kcr

:: DESCRIPTION

BERT-Kcr is a novel predictor for protein Kcr sites prediction, which was developed by using a transfer learning method with pre-trained bidirectional encoder representations from transformers (BERT) models.

::DEVELOPER

Zhu Lab

:: SCREENSHOTS

N/A

::REQUIREMENTS

Linux

:: DOWNLOAD

BERT-Kcr

:: MORE INFORMATION

Citation

Qiao Y, Zhu X, Gong H.
BERT-Kcr: Prediction of lysine crotonylation sites by a transfer learning method with pre-trained BERT models.
Bioinformatics. 2021 Oct 13:btab712. doi: 10.1093/bioinformatics/btab712. Epub ahead of print. PMID: 34643684.

ViennaRNA 2.5.0 – RNA Secondary Structure Prediction & Comparison

ViennaRNA 2.5.0

:: DESCRIPTION

ViennaRNA Package consists of a C code library and several stand-alone programs for the prediction and comparison of RNA secondary structures.

Vienna RNA WebServers

::DEVELOPER

Theoretical Biochemistry Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/ Mac OsX/ Windows

:: DOWNLOAD

Vienna RNA

:: MORE INFORMATION

Citation

Methods Mol Biol. 2015;1269:307-26. doi: 10.1007/978-1-4939-2291-8_19.
The ViennaRNA web services.
Gruber AR1, Bernhart SH, Lorenz R.

Ivo L. Hofacker
Vienna RNA secondary structure serverNucl.
Acids Res. (2003) 31 (13): 3429-3431

Lorenz, Ronny and Bernhart, Stephan H. and Höner zu Siederdissen, Christian and Tafer, Hakim and Flamm, Christoph and Stadler, Peter F. and Hofacker, Ivo L.
ViennaRNA Package 2.0
Algorithms for Molecular Biology, 6:1 26, 2011, doi:10.1186/1748-7188-6-26

PASTA 2.0 – Protein Aggregation Prediction

PASTA 2.0

:: DESCRIPTION

PASTA (Prediction of amyloid structure aggregation) is a web server for the analysis of amino acid sequences. It predicts which portions of a given input sequence are more likely to stabilize the cross-beta core of fibrillar aggregates.

::DEVELOPER

The BioComputing UP lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

PASTA

:: MORE INFORMATION

Citation:

PASTA 2.0: an improved server for protein aggregation prediction.
Walsh I, Seno F, Tosatto SC, Trovato A.
Nucleic Acids Res. 2014 Jul;42(Web Server issue):W301-7. doi: 10.1093/nar/gku399.

Antonio Trovato, Flavio Seno and Silvio C.E. Tosatto.
The PASTA server for protein aggregation prediction
Protein Engineering Design & Selection, 20(10):521-523. (2007)

RNAmigos – RNA Small Molecule Ligand Prediction

RNAmigos

:: DESCRIPTION

RNAmigos is a Graph Neural Network for predicting RNA small molecule ligands.

::DEVELOPER

Carlos Oliver

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / MacOsX
Python

:: DOWNLOAD

RNAmigos

:: MORE INFORMATION

Citation:

Oliver C, Mallet V, Gendron RS, Reinharz V, Hamilton WL, Moitessier N, Waldispühl J.
Augmented base pairing networks encode RNA-small molecule binding preferences.
Nucleic Acids Res. 2020 Aug 20;48(14):7690-7699. doi: 10.1093/nar/gkaa583. PMID: 32652015; PMCID: PMC7430648.

TSMDA – Target and Symptom-based computational model for miRNA-disease Association Prediction

TSMDA

:: DESCRIPTION

TSMDA is a novel machine learning method that leverages target and symptom information and negative sample selection to predict miRNA-disease association.

::DEVELOPER

Biosig Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Uthayopas K, de Sá AGC, Alavi A, Pires DEV, Ascher DB.
TSMDA: Target and symptom-based computational model for miRNA-disease-association prediction.
Mol Ther Nucleic Acids. 2021 Aug 26;26:536-546. doi: 10.1016/j.omtn.2021.08.016. PMID: 34631283; PMCID: PMC8479276.

epitope3D – Machine Learning method for conformational B-cell Epitope prediction

epitope3D

:: DESCRIPTION

epitope3D is a novel scalable machine learning method capable of accurately identifying conformational epitopes trained and evaluated on the largest curated epitope data set to date.

::DEVELOPER

Biosig Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

da Silva BM, Myung Y, Ascher DB, Pires DEV.
epitope3D: a machine learning method for conformational B-cell epitope prediction.
Brief Bioinform. 2021 Oct 21:bbab423. doi: 10.1093/bib/bbab423. Epub ahead of print. PMID: 34676398.

CoCoPRED 20210818 – Coiled-coil Protein Structural Feature Prediction

CoCoPRED 20210818

:: DESCRIPTION

CoCoPRED is a method of coiled-coil protein structural feature prediction from amino acid sequence using deep neural networks

::DEVELOPER

Computational Systems Biology Group, Shanghai Jiao Tong University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

CoCoPRED

:: MORE INFORMATION

Citation

Feng SH, Xia CQ, Shen HB.
CoCoPRED: coiled-coil protein structural feature prediction from amino acid sequence using deep neural networks.
Bioinformatics. 2021 Oct 30:btab744. doi: 10.1093/bioinformatics/btab744. Epub ahead of print. PMID: 34718416.

EditPredict – Prediction of RNA editable sites with convolutional Neural network

EditPredict

:: DESCRIPTION

EditPredict is a sequence-only, sequencing-independent tool, which can be used stand-alone to predict novel RNA editing and to assist in filtering for candidate RNA editing detected from RNA-Seq data.

::DEVELOPER

Steven Wong

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Python

:: DOWNLOAD

EditPredict

:: MORE INFORMATION

Citation

Wang J, Ness S, Brown R, Yu H, Oyebamiji O, Jiang L, Sheng Q, Samuels DC, Zhao YY, Tang J, Guo Y.
EditPredict: Prediction of RNA editable sites with convolutional neural network.
Genomics. 2021 Sep 23;113(6):3864-3871. doi: 10.1016/j.ygeno.2021.09.016. Epub ahead of print. PMID: 34562567.

preciseTAD 1.4.0 – Machine Learning framework for precise TAD Boundary Prediction

preciseTAD 1.4.0

:: DESCRIPTION

preciseTAD provides functions to predict the location of boundaries of topologically associated domains (TADs) and chromatin loops at base-level resolution.

::DEVELOPER

Mikhail Dozmorov <mikhail.dozmorov at gmail.com>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows / Linux
R
BioConductor

:: DOWNLOAD

preciseTAD

:: MORE INFORMATION

Citation:

Stilianoudakis SC, Marshall MA, Dozmorov MG.
preciseTAD: A transfer learning framework for 3D domain boundary prediction at base-pair resolution.
Bioinformatics. 2021 Nov 6:btab743. doi: 10.1093/bioinformatics/btab743. Epub ahead of print. PMID: 34741515.