JBEI-ICE, part registry platform and tools

The Joint BioEnergy Institute Inventory of Composable Elements (JBEI-ICEs) is an open source registry platform for managing information about biological parts. It is capable of recording information about ‘legacy’ parts, such as plasmids, microbial host strains and Arabidopsisseeds, as well as DNA parts in various assembly standards. ICE is built on the idea of a web of registries and thus provides strong support for distributed interconnected use. The information deposited in an ICE installation instance is accessible both via a web browser and through the web application programming interfaces, which allows automated access to parts via third-party programs. JBEI-ICE includes several useful web browser-based graphical applications for sequence annotation, manipulation and analysis that are also open source. As with open source software, users are encouraged to install, use and customize JBEI-ICE and its components for their particular purposes. As a web application programming interface, ICE provides well-developed parts storage functionality for other synthetic biology software projects. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects. The ICE software suite is available via Google Code (http://code.google.com/p/gd-ice/) , a hosting site for community-driven open source projects.

 

Apps Collections for Synthetic Biology

 

Synthetic biology which is inspired by “plug-and-play” concept is supported by standardized biobricks and also computational tools for analysis and optimization [1]. Here are bio-apps collections for you. Personally Tinkercell and UNAFold are mostly used.

Circuit design and simulation
 Biojade http://web.mit.edu/jagoler/www/biojade/
 Tinkercell http://www.tinkercell.com/Home
 Asmparts http://soft.synth-bio.org/asmparts.html
 ProMoT http://www.mpimagdeburg.mpg.de/projects/promot
 GenoCAD http://www.genocad.org/genocad/
 GEC http://research.microsoft.com/gec
 TABASCO http://openwetware.org/wiki/TABASCO#TabascoSimulator
 Hy3S http://hysss.sourceforge.net/index.shtml
Circuit optimization
 Genetdes http://soft.synth-bio.org/genetdes.html
 RoVerGeNe http://iasi.bu.edu/∼batt/rovergene/rovergene.htm
DNA and RNA design
 Gene Designer https://www.dna20.com/index.php?pageID=220
 GeneDesign http://www.genedesign.org
 UNAFold http://www.bioinfo.rpi.edu/applications/hybrid/download.php
 mfold http://mfold.bioinfo.rpi.edu/download/
 DINAMelt http://dinamelt.bioinfo.rpi.edu/
 Vienna RNA package http://www.tbi.univie.ac.at/∼ivo/RNA/
 Vienna RNA web servers http://rna.tbi.univie.ac.at/
 Zinc Finger Tools http://www.scripps.edu/mb/barbas/zfdesign/zfdesignhome.php
Protein design
 Rosetta http://www.rosettacommons.org/main.html
 RAPTOR http://www.bioinformaticssolutions.com/products/raptor/index.php
 HHpred http://toolkit.lmb.uni-muenchen.de/hhpred
 Modeler http://salilab.org/modeller/
 PFP http://dragon.bio.purdue.edu/pfp/
 Autodock 4.2 http://autodock.scripps.edu/
 HEX 5.1 http://webloria.loria.fr/∼ritchied/hex/
Integrated workflows
 SynBioSS http://synbioss.sourceforge.net/
 Clotho http://biocad-server.eecs.berkeley.edu/wiki/index.php/Tools
 Biskit http://biskit.sf.net

 

Suggested pages listing useful bio-apps maybe you will like in synthetic biology research:

  1. WikiGenes Toolbox ( http://www.wikigenes.org/e/art/e/187.html). As a free on-line tutorial edited by people all around the world, WikiGenes has spirits of Linux: open-source, sharing, interest, so is WikiGenes-Synthetic-Biology page. It enables you fast-learn what is synthetic life.
  2. OpenWetWare (http://openwetware.org/wiki/Computational_Tools).
  3. JCVI (http://www.jcvi.org/cms/research/software/#c614). This page is from J. Craig Venter Institute.

 

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[1] Marchisio, M. A., & Stelling, J. (2009). Computational design tools for synthetic biology. Current Opinion in Biotechnology, 20(4), 479-485. Retrieved from http://www.sciencedirect.com/science/article/pii/S0958166909001001

Computer Program Enrich Understandings to RNA motifs

DNA carries and passes the genetic information with nucleotides sequences, but in some virus RNA does the job instead of DNA.  In addition, the 3D structure of RNA, RNA motif, shows more various roles in cellular functions. It means that only with sequence information we cannot fully understand the RNA roles and functions.

Detecting and exploring RNA motif are prone to lie in modeling, engineering, and this is partly why we need computational biology.

RNA structural motifs are the building blocks of the complex RNA architecture. Identification of non-coding RNA structural motifs is a critical step towards understanding of their structures and functionalities. In this article, we present a clustering approach for de novo RNA structural motif identification. We applied our approach on a data set containing 5S, 16S and 23S rRNAs and rediscovered many known motifs including GNRA tetraloop, kink-turn, C-loop, sarcin–ricin, reverse kink-turn, hook-turn, E-loop and tandem-sheared motifs, with higher accuracy than the state-of-the-art clustering method. We also identified a number of potential novel instances of GNRA tetraloop, kink-turn, sarcin–ricin and tandem-sheared motifs. More importantly, several novel structural motif families have been revealed by our clustering analysis. We identified a highly asymmetric bulge loop motif that resembles the rope sling. We also found an internal loop motif that can significantly increase the twist of the helix. Finally, we discovered a subfamily of hexaloop motif, which has significantly different geometry comparing to the currently known hexaloop motif. Our discoveries presented in this article have largely increased current knowledge of RNA structural motifs.

Researchers at University of Central Florida [1] used a complex computer program to analyze RNA motifs — the subunits that make up RNA (ribonucleic acid).

–end &&reference

[1] C. Zhong, S. Zhang. Clustering RNA structural motifs in ribosomal RNAs using secondary structural alignment.Nucleic Acids Research, 2011; 40 (3): 1307 DOI:10.1093/nar/gkr804

 

FX: an RNA-Seq analysis tool on the cloud

FX is an RNA-Seq analysis tool, which runs in parallel on cloud computing infrastructure, for the estimation of gene expression levels and genomic variant calling. In the mapping of short RNA-Seq reads, FX uses a transcriptome-based reference primarily, generated from ∼160,000 mRNA sequences from RefSeq, UCSC and Ensembl databases. This approach reduces the misalignment of reads originating from splicing junctions. Unmapped reads not aligned on known transcripts are then mapped on the human genome reference. FX allows analysis of RNA-Seq data on cloud computing infrastructures, supporting access through a user-friendly web interface.

FX is freely available on the web at (http://fx.gmi.ac.kr), and can be installed on local Hadoop clusters. Guidance for the installation and operation of FX can be found under the ‘Documentation’ menu on the website.