Tag: Identifying

PlantPAN 2.0 – Identifying Combinatorial Cis-regulatory Elements with Distance Constraint in Plant Gene Groups

PlantPAN 2.0

:: DESCRIPTION

PlantPAN (Plant Promoter Analysis Navigator) is a database-assisted system for recognizing combinatorial cis-regulatory elements with distance constraint in plant co-expressed genes.

::DEVELOPER

Integrative System Biology Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

PlantPAN 2.0: an update of plant promoter analysis navigator for reconstructing transcriptional regulatory networks in plants.
Chow CN, Zheng HQ, Wu NY, Chien CH, Huang HD, Lee TY, Chiang-Hsieh YF, Hou PF, Yang TY, Chang WC.
Nucleic Acids Res. 2015 Oct 17. pii: gkv1035.

BMC Genomics. 2008 Nov 26;9:561. doi: 10.1186/1471-2164-9-561.
PlantPAN: Plant promoter analysis navigator, for identifying combinatorial cis-regulatory elements with distance constraint in plant gene groups.
Chang WC, Lee TY, Huang HD, Huang HY, Pan RL.

TreeGibbsSampler – Identifying Conserved Motifs without Aligning Orthologous Sequences

TreeGibbsSampler

:: DESCRIPTION

Tree Gibbs Sampler is a software for identifying motifs by simultaneously using the motif overrepresentation property and the motif evolutionary conservation property. It identifies motifs without depending on pre-aligned orthologous sequences, which makes it useful for the extraction of regulatory elements in multiple genomes of both closely related and distant species.

::DEVELOPER

Xiaohui Cai, Haiyan Nancy Hu ,Xiaoman Shawn Li

:: SCREENSHOTS

TreeGibbsSampler

:: REQUIREMENTS

  • Linux/ Windows

:: DOWNLOAD

 Tree Gibbs Sampler

:: MORE INFORMATION

Citation:

Bioinformatics. 2007 Aug 1;23(15):2013-4. Epub 2007 May 31.
Tree Gibbs Sampler: identifying conserved motifs without aligning orthologous sequences.
Cai X, Hu H, Li XS.

EPIG-Seq v1.0 – Extracting Patterns and Identifying co-expressed Genes from RNA-Seq

EPIG-Seq v1.0

:: DESCRIPTION

EPIG-Seq is an algorithm and software to identify gene expression patterns from RNA-Seq count data. Once the patterns are identified, co-expressed genes are clustered to the patterns.

::DEVELOPER

EPIG-Seq team

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows
  • Java

:: DOWNLOAD

EPIG-Seq

:: MORE INFORMATION

Citation:

BMC Genomics. 2016 Mar 22;17:255. doi: 10.1186/s12864-016-2584-7.
EPIG-Seq: extracting patterns and identifying co-expressed genes from RNA-Seq data.
Li J, Bushel PR.

Segment 1.04 – Identifying Compositional Domains in DNA Sequences

Segment 1.04

:: DESCRIPTION

Segment is a heuristic segmentation algorithm for DNA sequences. The program divides a DNA sequence into compositionally homogeneous domains by iterating a local optimization procedure at a given statistical significance.

::DEVELOPER

The group of computational genomics and bioinformatics at Granada University (Spain)

:: SCREENSHOTS

Segment

:: REQUIREMENTS

  • Windows 

:: DOWNLOAD

 Segment

:: MORE INFORMATION

Citation:

Oliver JL, Román-Roldán R, Pérez J, Bernaola-Galván P. 1999.
SEGMENT: identifying compositional domains in DNA sequences.
Bioinformatics 15: 974-979

PHYPred – Identifying Phage Enzymes and Hydrolases

PHYPred

:: DESCRIPTION

The web-server PHYPred was developed to identify the phage enzymes and hydrolases based on the sequence information.

::DEVELOPER

LinDing Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

PHYPred: a tool for identifying bacteriophage enzymes and hydrolases.
Ding H, Yang W, Tang H, Feng PM, Huang J, Chen W, Lin H.
Virol Sin. 2016 Aug;31(4):350-2. doi: 10.1007/s12250-016-3740-6.

iRNAD – Identifying D Modification Sites in RNA sequence

iRNAD

:: DESCRIPTION

iRNAD is a system for identifying whether a RNA sequence contains D modification sites based on machine learning method.

::DEVELOPER

LinDing Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

iRNAD: a computational tool for identifying D modification sites in RNA sequence.
Xu ZC, Feng PM, Yang H, Qiu WR, Chen W, Lin H.
Bioinformatics. 2019 May 11. pii: btz358. doi: 10.1093/bioinformatics/btz358.

iRSpot-Pse6NC 2.0 – Identifying Recombination Hotspots in Saccharomyces Cerevisiae

iRSpot-Pse6NC 2.0

:: DESCRIPTION

Based on dataset containing both ORF and non-ORF recombination sites, iRSpot-Pse6NC is a predictor which using SVM classifier by incorporating the key hexamer features into the general PseKNC (Pseudo K-tuple Nucleotide Composition) via the binomial distribution feature selection approach.

::DEVELOPER

LinDing Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

A comparison and assessment of computational method for identifying recombination hotspots in Saccharomyces cerevisiae.
Yang H, Yang W, Dao FY, Lv H, Ding H, Chen W, Lin H.
Brief Bioinform. 2019 Oct 21. pii: bbz123. doi: 10.1093/bib/bbz123

iRSpot-Pse6NC: Identifying recombination spots in Saccharomyces cerevisiae by incorporating hexamer composition into general PseKNC.
Int J Biol Sci. 2018 May 22;14(8):883-891. doi: 10.7150/ijbs.24616. eCollection 2018.
Yang H, Qiu WR, Liu G, Guo FB, Chen W, Chou KC, Lin H.

iACP – A sequence-based tool for Identifying Anticancer Peptides

iACP

:: DESCRIPTION

The web-server iACP was developed to identify the anticancer peptides based on the sequence information.

::DEVELOPER

LinDing Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

iACP: a sequence-based tool for identifying anticancer peptides.
Chen W, Ding H, Feng P, Lin H, Chou KC.
Oncotarget. 2016 Mar 1. doi: 10.18632/oncotarget.7815.

CaLecPred – A Sequence-based Predictor for Identifying Cancerlectin

CaLecPred

:: DESCRIPTION

The web-server CalecPred was developed to identify cancerlectin based on the sequence information.

::DEVELOPER

LinDing Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Predicting cancerlectins by the optimal g-gap dipeptides.
Lin H, Liu WX, He J, Liu XH, Ding H, Chen W.
Sci Rep. 2015 Dec 9;5:16964. doi: 10.1038/srep16964.

MOITF-EM – Automated Computational Tool for Identifying Conserved Domains in CryoEM Structures

MOITF-EM

:: DESCRIPTION

MOTIF-EM is an automated computational tool for identifying regions or domains or motifs in cryoEM maps of large macromolecular assemblies (such as chaperonins, viruses, etc.)

::DEVELOPER

Mitul Saha

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

  MOITF-EM 

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Jun 15;26(12):i301-9. doi: 10.1093/bioinformatics/btq195.
MOTIF-EM: an automated computational tool for identifying conserved regions in CryoEM structures.
Saha M, Levitt M, Chiu W.