OpenGrowth 1.0.1 – Construct de novo Ligands for Protein

OpenGrowth 1.0.1

:: DESCRIPTION

OpenGrowth is a research program which grows new ligands in proteins by connecting small organic fragments.

::DEVELOPER

The Shakhnovich Biophysics Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • MacOsX / Linux

:: DOWNLOAD

 OpenGrowth

:: MORE INFORMATION

Citation

OpenGrowth: An Automated and Rational Algorithm for Finding New Protein Ligands.
Chéron N, Jasty N, Shakhnovich EI.
J Med Chem. 2015 Sep 23

DNN-HMM – De novo Identification of Replication-timing Domains in the Human Genome

DNN-HMM

:: DESCRIPTION

DNN-HMM (deep neural network and a hidden Markov model) is a novel hybrid architecture combining a pre-trained,for the de novo identification of replication domains using replication timing profiles.

::DEVELOPER

DNN-HMM team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • MatLab / Perl

:: DOWNLOAD

  DNN-HMM

:: MORE INFORMATION

Citation

De novo Identification of replication-timing domains in the human genome by deep learning.
Liu F, Ren C, Li H, Zhou P, Bo X, Shu W.
Bioinformatics. 2015 Nov 5. pii: btv643.

Telescoper 0.2 – De novo Assembly Algorithm

Telescoper 0.2

:: DESCRIPTION

Telescoper is a local assembly algorithm designed for short-reads from NGS platforms such as Illumina. The reads must come from two libraries: one short insert, and one long insert.

::DEVELOPER

Yun S. Song

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

 Telescoper

:: MORE INFORMATION

Citation

Bresler, M., Sheehan, S., Chan, A.H., and Song, Y.S.
Telescoper: De novo Assembly of Highly Repetitive Regions.
Bioinformatics, 28 (2012) i311-i317.

TGNet – Visualization and Quality Assessment of de novo Genome Assemblies

TGNet

:: DESCRIPTION

TGNet is a Cytoscape-based tool for visualization and quality assessment of de novo genome assemblies. Specifically it facilitates rapid detection of inconsistencies between a genome assembly and an independently derived transcriptome assembly.

::DEVELOPER

Wurm Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Java
  • Cytoscape

:: DOWNLOAD

 TGNet

:: MORE INFORMATION

Citation

Bioinformatics. 2011 Dec 15;27(24):3425-6. doi: 10.1093/bioinformatics/btr569. Epub 2011 Oct 12.
Visualization and quality assessment of de novo genome assemblies.
Riba-Grognuz O, Keller L, Falquet L, Xenarios I, Wurm Y.

LTRsift 1.0.2 – Postprocessing of de novo predicted LTR Retrotransposon Annotations

LTRsift 1.0.2

:: DESCRIPTION

LTRsift is a graphical desktop tool for semi-automatic postprocessing of de novo predicted LTR retrotransposon annotations, such as the ones generated by LTRharvest and LTRdigest.

::DEVELOPER

RESEARCH GROUP FOR GENOME INFORMATICS ,Center for Bioinformatics, University of Hamburg

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / MacOsX

:: DOWNLOAD

LTRsift

:: MORE INFORMATION

Citation:

S. Steinbiss, S. Kastens and S. Kurtz:
LTRsift: a graphical user interface for semi-automatic classification and postprocessing of de novo detected LTR retrotransposons.
Mobile DNA, 3:18 (2012)

W-ChIPMotifs – de novo Motif Discovery from ChIP-based High throughput data

W-ChIPMotifs

:: DESCRIPTION

W-ChIPMotifs is a web application tool for de novo motif discovery from ChIP-based high throughput data.

::DEVELOPER

Jin Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

W-ChIPMotifs: a web application tool for de novo motif discovery from ChIP-based high-throughput data.
Jin VX, Apostolos J, Nagisetty NS, Farnham PJ.
Bioinformatics. 2009 Dec 1;25(23):3191-3.

miniasm v0.3- Fast Overlapped-based de novo Assembler for Noisy long Reads

miniasm v0.3

:: DESCRIPTION

Miniasm is a very fast OLC-based de novo assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by minimap) as input and outputs an assembly graph in the GFA format.

::DEVELOPER

Heng Li

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

Miniasm

:: MORE INFORMATION

Citation

Li H.
Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences.
Bioinformatics. 2016 Jul 15;32(14):2103-10. doi: 10.1093/bioinformatics/btw152. Epub 2016 Mar 19. PMID: 27153593; PMCID: PMC4937194.

DNMFilter 0.1.1 – De Novo Mutation Filter

DNMFilter 0.1.1

:: DESCRIPTION

DNMFilter is a machine learning based tool designed to filter out false positive de novo mutations (DNMs) obtained by any computational or manual approaches from next generation sequencing data.

::DEVELOPER

DNMFilter team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Java
  • Python

:: DOWNLOAD

 DNMFilter

:: MORE INFORMATION

Citation

Bioinformatics. 2014 Mar 27.
A gradient-boosting approach for filtering de novo mutations in parent-offspring trios.
Liu Y1, Li B, Tan R, Zhu X, Wang Y.

Oases 0.2.09 – De novo Transcriptome Assembler for very short reads

Oases 0.2.09

:: DESCRIPTION

Oases designed to heuristically assemble RNA-seq reads in the absence of a reference genome, across a broad spectrum of expression values and in presence of alternative isoforms. It achieves this by using an array of hash lengths, a dynamic filtering of noise, a robust resolution of alternative splicing events, and the efficient merging of multiple assemblies. It was tested on human and mouse RNA-seq data and is shown to improve significantly on the transABySS and Trinity de novo transcriptome assemblers.

::DEVELOPER

Daniel Zerbino

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 Oases

:: MORE INFORMATION

Citation

Marcel H. Schulz, Daniel R. Zerbino, Martin Vingron and Ewan Birney
Oases: Robust de novo RNA-seq assembly across the dynamic range of expression levels
Bioinformatics (2012)doi: 10.1093/bioinformatics/bts094

MonSTR 1.0.0 – Toolkit for Calling and analyzing de novo STR mutations

MonSTR 1.0.0

:: DESCRIPTION

MonSTR is a tool for calling de novo mutations from HipSTR or GangSTR VCF files.)

::DEVELOPER

Gymrek Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

MonSTR

:: MORE INFORMATION

Citation

Mitra I, Huang B, Mousavi N, Ma N, Lamkin M, Yanicky R, Shleizer-Burko S, Lohmueller KE, Gymrek M.
Patterns of de novo tandem repeat mutations and their role in autism.
Nature. 2021 Jan;589(7841):246-250. doi: 10.1038/s41586-020-03078-7. Epub 2021 Jan 13. PMID: 33442040; PMCID: PMC7810352.