DNAMA
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Revision as of 13:43, 20 February 2012
General Information
- Application's name: DNA Multicore Analysis
- Application's acronym: DNAMA
- Virtual Research Community: Life Sciences
- Scientific contact: Danilo Mrdak, danilomrdak@gmail.com
- Technical contact: Luka Filipovic, lukaf@ac.me
- Developers: Center of Information System & Faculty of Natural Sciences - University of Montenegro
- Web site: ...
Short Description
Using of Network Cluster Web with potential of super-computer performances for DNA sequences analyzing will give us unlimited potential for DNA research. This will give us unlimited potential in term of analyzed sequence number and time consumption for analysis to be carried out. As many of DNA comparing and analyzing software use Monte Carlo and Markov chain algorithms that are time consuming regarding to sequence numbers, super-computer resource will faster our job and make the robust and overall analysis possible.Using of all published sequences for one group (e.g. for all salmonid species: salmons, trout, grayling, river huchon) from the same DNA region (mitochondrial D-loop DNA, Cytochrom b gene…) will give us more detailed insight in their relationships and phylogeny relationships.
DNAMA application is based on RAxML application from The Exelixis Lab.
Problems Solved
The working resource that is possible to use trough network computer clustering will allow us to put in analysis as much samples as we wish and that those analysis will be finished in one to few hours. Moreover, we will tray to modified the algorithms in order to have multi-loci analysis to get a consensus three that will suggest the most possible pathways of phylogeny with much higher level of confidence
Scientific and Social Impact
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Collaborations
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Beneficiaries
- University of Montenefro - Faculty of Natural sciences - Biology Department
Number of users
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Development Plan
- Concept: before start of project - finished by RAxML developers
- Start of alpha stage: ...
- Start of beta stage: 09.2010
- Start of testing stage: 03.2011
- Start of deployment stage: 11.2011
- Start of production stage: 11.2011
Resource Requirements
- Number of cores required for a single run: 16-512
- Minimum RAM/core required: 1 GB
- Storage space during a single run: 256 MB
- Long-term data storage: 1 GB
- Total core hours required: ...
Technical Features and HP-SEE Implementation
- Primary programming language: C
- Parallel programming paradigm: MPI, OpenMPI
- Main parallel code: MPI, OpenMPI
- Pre/post processing code: C, Dendroscope (for visualization for results)
- Application tools and libraries: RAxML
Usage Example
Execution from command line : /opt/exp_software/mpi/mpiexec/mpiexec-0.84-mpich2-pmi/bin/mpiexec -np 128 /home/lukaf/raxml/RAxML-7.2.6/raxmlHPC-MPI -m GTRGAMMA -s /home/lukaf/raxml/trutte_input.txt -# 1000 -n T16x8
Infrastructure Usage
- Home system: HPCG, Bulgaria
- Applied for access on: 05.2011
- Access granted on: 05.2011
- Achieved scalability: up to 128 cores
- Accessed production systems:
- ...
- Applied for access on: ...
- Access granted on: ...
- Achieved scalability: ... cores
- ...
- Applied for access on: ...
- Access granted on: ...
- Achieved scalability: ... cores
- Porting activities: ...
- Scalability studies: ...
Running on Several HP-SEE Centres
- Benchmarking activities and results: ...
- Other issues: ...
Achieved Results
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Publications
- ...
- ...
Foreseen Activities
- data analysis for new DNA sequences
- multigene analysys (mt DNA, Cut B. … )
- Hybrid RAxML testing