Bosc2011 ntino-krampis-full
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Cloud BioLinux provides an open source and fully customizable bioinformatics computing environment on the cloud for genomics research. It allows small labs to perform large-scale genomic analyses independently without dedicated on-site computing resources. The project is a community effort led by Ntino Krampis and developed by a core team, with contributions from bioinformaticians worldwide. Cloud BioLinux builds on existing open source tools by providing pre-configured virtual machines on Amazon Web Services that can be easily deployed through a desktop computer with an internet connection. This allows researchers to share projects, analyses, and computing environments with collaborators through whole-system snapshots.
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This document discusses the Microsoft Biology Foundation (MBF), an open source bioinformatics toolkit built on the .NET Framework. MBF provides components for working with biological data formats, sequences, and algorithms. It is intended as a foundation for other tools and applications to build upon, rather than an application itself. The community around MBF consists of scientific programmers with a range of expertise. MBF is cross-platform, with new features in version 2 including advanced math functions, comparative assembly, command line tools, and visualization capabilities. The source code and community are hosted on Codeplex to encourage open source development of the toolkit.
Mobyle 1 0_new_features_new_types_of_service
Mobyle 1.0 introduces new features including workflows, viewers, and improved workspace management. Workflows allow automated chaining of sequential or parallel jobs specified through an XML description. Viewers display specialized output like VARNA diagrams through custom HTML code. Authentication and reporting have also been expanded with OpenID and Google Analytics integration.
Bosc2011 isobar-fbp
The document describes an R package called isobar that provides tools for analyzing quantitative proteomics data from isobaric labeling experiments. The package extracts identification and quantitative information from mass spectrometry data. It models technical variability, normalizes data, and handles biological variability to determine differential protein expression accurately. Statistical tests and data visualization help decide significant regulation. Automated reporting of results in PDF format via Sweave is demonstrated.
Talk6 biopython bosc2011
1) Biopython is a free and open source library for bioinformatics written in Python. It has regular releases and is supported by an international team of volunteer developers.
2) Recent Biopython releases include versions 1.55-1.57, which added new features like Python 3 support, command line wrappers, and SQLite sequence indexing.
3) Biopython has participated in Google Summer of Code for the past two years, funding student projects on topics like PDB parsing and biomolecular interface analysis. Integrated testing via Buildbot helps ensure high code quality.
Unipro ugene bosc 2011 update
UGENE is a multiplatform open-source toolkit for complex genome analysis. It integrates popular bioinformatics tools into a unified visual and computational solution. Written in C++/Qt, UGENE has a modular structure and integrated plugin system. It supports over 20 common biological data formats and allows users to retrieve information from remote databases. UGENE features rich visualization capabilities and algorithms optimized for multi-core CPUs and GPUs. The UGENE Workflow Designer provides a visual environment for constructing computational workflows combining algorithms, data formats, and high performance capabilities.
Bosc talk 7-15-2011x
Cytoscape is a popular open-source software for biological network visualization and analysis. It has a large plugin ecosystem that allows for customization but this has led to issues with backwards compatibility and maintenance over time. Cytoscape 3.0 aims to address these issues by implementing a new architecture based on OSGi, semantic versioning, and Maven to better define dependencies, enforce modularity, and make developing and maintaining plugins easier going forward. This involves rewriting parts of Cytoscape but is intended to improve the sustainability and extensibility of the software long-term.
B07-GenomeContent-Biomart
BioMart 0.8 offers new features like an integrated tool for building and configuring BioMart servers, support for more database backends, and analysis and visualization plugins. It provides more flexible querying interfaces like diverse web GUIs and programmatic APIs. BioMart hides the complexity of underlying databases and provides a simple conceptual model with concepts like datasets, attributes, and filters. It is used by several large collaborative projects for data management and federation.
B03-GenomeContent-Intermine
The document discusses how InterMine uses RESTful web services for data integration and interoperability between biological databases, providing examples of how the InterMine API can be used to query databases and manage workflows through client libraries and sugar syntax. It also covers lessons learned in developing InterMine including using JSON for data exchange and implementing token-based authentication.
F06-Cloud-Enabling NGS
This document summarizes a presentation about CloudMan, a platform for deploying cloud computing resources and Galaxy instances. CloudMan allows users to setup cloud clusters in minutes without expertise, provides over 700GB of reference genomes and bioinformatics tools, and enables customization and sharing of derived cluster instances. It bridges users, isolated Galaxy instances, and cloud infrastructure. Key features include deployment on AWS, automated configuration, dynamic storage, and elastic scaling of resources.
D03-NextGen-Bio-NGS
This document describes Bio-NGS, a BioRuby plugin for conducting programmable workflows for Next Generation Sequencing (NGS) data. Bio-NGS provides a software development framework, application, and project environment for analyzing NGS data. It integrates third-party bioinformatics tools as wrappers or bindings and allows for modular, reusable plugins. The document outlines features of the Bio-NGS application, software development framework, and project environment.
F01-Cloud-Mygene.info
This document describes MyGene.Info, a gene annotation service that provides gene data through a RESTful API. It discusses how gene data is stored and queried from a CouchDB document-oriented database. Users can search for genes and retrieve full or filtered annotation objects for specific genes in JSON format through HTTP requests to the MyGene.Info website. The service aims to allow quick development of gene-centric websites and applications without needing to maintain a local gene annotation database.
A01-Openness in knowledge-based systems
This document discusses the potential for open source artificial intelligence to help understand molecular biology data. It argues that capturing common sense knowledge computationally has been challenging, but knowledge about molecular biology exists explicitly. An open source AI focused on molecular biology could help explain genomic data by developing a comprehensive knowledge base and using abductive inference. However, explaining biological phenomena is difficult and requires judgment. The document advocates for open source development to gain productivity advantages and build trust through transparency. It outlines challenges and opportunities for facilitating an open source AI community focused on understanding life.
F03-Cloud-Obiwee
OBIWEE is an open source bioinformatics cloud environment for running intensive workflows. It uses SLICEE as a workflow authoring tool and runs jobs on a scalable virtual cluster deployed on private or public clouds using OpenNebula or EC2. Workflows are authored by describing command lines and OBIWEE handles parallelization and job submission to the cluster. It provides tools for deployment, data management, and client access via command line or GUI interfaces like Kepler.
C02-Visualization-Applying visual analytics
Applying visual analytics to extend the genome browser from visualisation tool to analysis tool (Jeremy Goecks)
B04-GenomeContent-EasyDAS
The document discusses easyDAS, which is a tool that automatically creates DAS servers to provide access to biological data. It allows users without programming experience to quickly setup a DAS server without managing server installation or data storage. However, easyDAS has limitations in terms of dataset size and flexibility compared to custom DAS servers. The document provides guidance on when easyDAS is appropriate to use and also describes how to install a custom easyDAS server.
G07-Misc-Gmod
The document provides updates on the GMOD project, including new developments to the Chado schema, Tripal toolkit, GBrowse genome browser, and efforts to deploy GMOD tools on cloud platforms. Key updates include a new natural diversity Chado module, improved features in Tripal 0.3b like loaders and custom templates, new user account options in GBrowse2, and work to provide pre-configured GMOD server images on Amazon Web Services. The document acknowledges funding sources and contributors to ongoing work.
G09-Misc-EMBOSS
EMBOSS is an open source software suite for biological sequence analysis. The document provides an update on EMBOSS release 6.4.0 in July 2011, including new features like additional data sources and ontologies, a new query language, and enhanced installation and interfaces to improve usability. It acknowledges contributions from various organizations that support ongoing development of EMBOSS.
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Bosc2011 ntino-krampis-full
- 1. Cloud BioLinux: open source, fully-customizable bioinformatics computing on the cloud for the genomics community and beyond BOSC 2011 - Vienna, Austria Ntino Krampis, PhD Asst. Professor J. Craig Venter Institute (JCVI) agbiotec@gmail.com
- 2. The community is what makes an open source project Brad Chapman, Tim Booth, Mesude Bicak, Dawn Field, Dan Pass – core development and planning Enis Afgan, Pjotr Prins, Stephen Möller - and all other members of the cloud biolinux community that move it fwd J. Craig Venter Inst. - time allowed to work on an open-source project
- 3. Expensive sequencing and large organizations Commodity sequencing and small labs ● large sequencing center, multi-million, broad-impact sequencing projects ● dedicated bioinformatics department, compute clusters ● small-factor, bench-top sequencer available: GS Junior by 454 ● sequencing as a standard technique in basic biology and genetics research ● RNAseq and ChiPseq, and each biologist will be tackling a metagenome
- 4. Will small labs become the long tail of sequencing ? amount of sequencing Credit: WikiMedia Commons number of labs
- 5. “Bioinformatics nation is a land of city-states” Lincoln Stein ● small labs building small-scale bioinformatics infrastructures ● duplication of effort in compiling and installing software tools ● some groups have no hardware, expertise, or time to install and run software ● NEBC BioLinux ( tinyurl.com/BioLinux-NEBC ) 100+ pre-configured tools ● example: glimmer, hmmer, phylip, rasmol, genespring, clustalw, EMBOSS how about large-scale sequence datasets ?
- 6. Cloud BioLinux pre-configured and on-demand bioinformatics computing on the cloud ● JCVI cloud computing research ● NEBC BioLinux software repository + ● community effort – Hackathon / BOSC 2010 - 11 ● Virtual Machine (VM) on Amazon cloud large-scale computing independently of = ● institutional or geographic boundaries ● only need a desktop computer with internet access cloudbiolinux.org
- 7. simple for end-users signup at aws.amazon.com http://tinyurl.com/cloud-biolinux-tutorial
- 8. Amazon EC2 → linux desktop via remote desktop client
- 9. What if I want to share my alignments with a collaborator? save your data as a new VM 0.10$ / GB / month at 15GB, it costs 1.5$ / month
- 10. “whole system snapshot exchange” (Dudley and Butte 2010) capture the state of the computing system and data software execution parameters and “massaged” input datasets
- 11. Cloud BioLinux developer's framework create cloud VM / images with standardized software configurations ● customize Cloud BioLinux based on community requirements ● mix and match software from NEBC or other (DebianMed, Scientific Linux etc.) ● share customized VMs with collaborators, avoiding effort duplication ● deploy Cloud BioLinux on private and local clouds
- 12. software domains in bioinformatics: nextgen sequencing, de novo assembly, annotation, phylogeny, molecular structures, gene expression analysis github.com/chapmanb/cloudbiolinux
- 13. Cloud BioLinux developer's framework ● based on python-fabric auto-deployment tool ● software components listed in plain text files ● collaborators use files to share descriptions of cloud VM / images ● start with a bare-bones VM / image ● fabric downloads and installs specified software tinyurl.com/python-fabric
- 14. Cloud Biolinux The future ● groups.google.com/cloudbiolinux and cloudbiolinux.org ● expand community, receive feedback, add more software to the VM ● scalable computing: SGE (Galaxy Cloudman), Hadoop (cloudgene.uibk.ac.at) ● add next-gen sequencing pipelines, NIH funding - adds effort in development ● We just had a 2-day codefest at the MetaLab, http://metalab.at/
- 15. and before I finish this talk....
- 20. Thank you !