IDP-Seq2Seq – Identification of Intrinsically Disordered Proteins and Regions based on Sequence to Sequence Learning

IDP-Seq2Seq

:: DESCRIPTION

IDP-Seq2Seq applied the Sequence to Sequence Learning (Seq2Seq) derived from natural language processing (NLP) to map protein sequences to “semantic space” to reflect the structure patterns with the help of predicted Residue-Residue Contacts (CCMs) and other sequence-based features. Furthermore, the Attention mechanism was employed to capture the global associations between all residue pairs in the proteins.

::DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Tang YJ, Pang YH, Liu B.
IDP-Seq2Seq: identification of intrinsically disordered regions based on sequence to sequence learning.
Bioinformatics. 2021 Jan 29;36(21):5177-5186. doi: 10.1093/bioinformatics/btaa667. PMID: 32702119.

BamReadCount 0.01 – Calculate Read Count for each region in the input list of Regions

BamReadCount 0.01

:: DESCRIPTION

The tool BamReadCount calculates the number of reads covering a list of input regions and the normalized read count w.r.t total mapped reads and region length. It also outputs the GC content of each region and the associated read count in the corresponding GC bin, which will be used for correcting the GC bias.

::DEVELOPER

BamReadCount team

:: SCREENSHOTS

N/A

::REQUIREMENTS

Linux

:: DOWNLOAD

BamReadCount

:: MORE INFORMATION

GISTIC 2.0.23 – Detect Regions of Significant Copy-number Gains and Losses

GISTIC 2.0.23

:: DESCRIPTION

GISTIC (Genomic Identification of Significant Targets in Cancer) facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers

::DEVELOPER

The Cancer Genome Analysis (CGA) group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

GISTIC

:: MORE INFORMATION

Citation

Genome Biol. 2011;12(4):R41. Epub 2011 Apr 28.
GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers.
Mermel CH, Schumacher SE, Hill B, Meyerson ML, Beroukhim R, Getz G.

REX – Region Evolution eXplorer

REX

:: DESCRIPTION

REX is a web-based system for exploring the evolution of ontology parts (regions).

::DEVELOPER

Interdisciplinary Centre for Bioinformatics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Region Evolution eXplorer – A tool for discovering evolution trends in ontology regions.
Christen V, Hartung M, Groß A.
J Biomed Semantics. 2015 Jun 1;6:26. doi: 10.1186/s13326-015-0020-6. eCollection 2015.

pfilt 1.5 – Sequence Filtering for Low-complexity, Coiled-coil and Biased Amino Acid Regions

pfilt 1.5

:: DESCRIPTION

pfilt program is designed to mask out (i.e. replace amino acid characters with Xs) regions of low complexity, coiled-coil regions and regions with extremely biased amino acid compositions. For compositional biased regions,only the overrepresented amino acids are masked.

:DEVELOPER

Bioinformatics Group – University College London

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

pfilt

:: MORE INFORMATION

Citation:

Jones, D.T. & Swindells, M.B. (2002)
Getting the most from PSI-BLAST.
Trends Biochem Sci. 2002 Mar;27(3):161-4.

AIRlINER – Assessment of A-to-I RNA Editing Sites in Non-repetitive Regions

AIRlINER

:: DESCRIPTION

AIRlINER is an algorithmic approach to the assessment of A-to-I (Adenosine-to-Inosine) RNA editing sites in non-repetitive regions. It determines the editing probability of an adenosine by analyzing its flanking region of 10 nucleotides. Such pattern is then combined with a similar model calculated from un-edited sequences, resulting in the estimation of an unbiased editing probability.

::DEVELOPER

AIRlINER team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation:

Knowledge in the Investigation of A-to-I RNA Editing Signals.
Nigita G, Alaimo S, Ferro A, Giugno R, Pulvirenti A.
Front Bioeng Biotechnol. 2015 Feb 24;3:18. doi: 10.3389/fbioe.2015.00018.

REPPER – Detect Regions with Short Gapless REPeats in Protein Sequences

REPPER

:: DESCRIPTION

REPPER (REPeats and their PERiodicities) is an integrated server that detects and analyzes regions with short gapless repeats in protein sequences or alignments. It finds periodicities by Fourier Transform (FTwin) and internal similarity analysis (REPwin). FTwin assigns numerical values to amino acids that reflect certain properties, for instance hydrophobicity, and gives information on corresponding periodicities. REPwin uses self-alignments and displays repeats that reveal significant internal similarities. Both programs use a sliding window to ensure that different periodic regions within the same protein are detected independently. FTwin and REPwin are complemented by secondary structure prediction (PSIPRED) and coiled coil prediction (COILS), making the server a versatile analysis tool for sequences of fibrous proteins.

::DEVELOPER

Söding Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation:

M.Gruber, J. Söding , and A.N.Lupas (2005)
REPPER – repeats and their periodicities in fibrous proteins
Nucl. Acids Res., 33(2), W239-43

Pro-Coffee – Aligns Homologous Promoter Regions

Pro-Coffee

:: DESCRIPTION

Pro-Coffee is a multiple aligner specifically designed for homologous promoter regions.

::DEVELOPER

Notredame’s Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation:

Nucleic Acids Res. 2012 Apr;40(7):e52. doi: 10.1093/nar/gkr1292. Epub 2012 Jan 9.
Use of ChIP-Seq data for the design of a multiple promoter-alignment method.
Erb I, González-Vallinas JR, Bussotti G, Blanco E, Eyras E, Notredame C.

DiNuP 1.3 – Identify Regions of Differential Nucleosome Positioning

DiNuP 1.3

:: DESCRIPTION

DiNuP compares the nucleosome profiles generated by high-throughput sequencing between different conditions. DiNuP provides a statistical p-value for each identified RDNP based on the difference of read distributions. DiNuP also empirically estimates the FDR as a cutoff when two samples have different sequencing depths and differentiate reliable RDNPs from the background noise. Evaluation of DiNuP showed it to be both sensitive and specific for the detection of changes in nucleosome location, occupancy and fuzziness. RDNPs that were identified using publicly available datasets revealed that nucleosome positioning dynamics are closely related to the epigenetic regulation of transcription.

::DEVELOPER

Zhang Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Python

:: DOWNLOAD

DiNuP

:: MORE INFORMATION

Citation

Fu K, Tang Q, Feng J, Liu XS, Zhang Y.
DiNuP: a systematic approach to identify regions of differential nucleosome positioning.
Bioinformatics 2012; 28(15):1965-71.

RegionalHapMapExtractor – Extract a Region from HapMapII for MaCH imputation

RegionalHapMapExtractor

:: DESCRIPTION

RegionalHapMapExtractor is a software to extract a region from hapMapII for MaCH imputation

::DEVELOPER

Yun Li

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows / MacOsX
Perl

:: DOWNLOAD

RegionalHapMapExtractor

:: MORE INFORMATION