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Global-scale distributed I/O with ParaMEDIC

P. Balaji, W. Feng, H. Lin, J. Archuleta, S. Matsuoka, A. Warren, J. Setubal, Ewing Lusk, R. Thakur, I. Foster, D. S. Katz, S. Jha (+3 others)
2010 Concurrency and Computation  
Achieving high performance for distributed I/O on a wide-area network continues to be an elusive holy grail.  ...  The overall project involved nine computational sites spread across the U.S. and generated more than a petabyte of data that was 'teleported' to a large-scale facility in Tokyo for storage.  ...  In the following sections, we address the issues with working on such a large-scale distributed system that are not immediately apparent on smaller-scale systems.  ... 
doi:10.1002/cpe.1590 fatcat:fwkfljwcpbeaxbrhunsuxxado4

Sign: large-scale gene network estimation environment for high performance computing

Yoshinori Tamada, Teppei Shimamura, Rui Yamaguchi, Seiya Imoto, Masao Nagasaki, Satoru Miyano
2011 Genome Informatics Series  
All these models require a huge amount of computational resources for estimating large-scale gene networks and therefore are designed to be able to exploit the speed of 10 petaflops.  ...  Our research group is currently developing software for estimating large-scale gene networks from gene expression data.  ...  Computational time was provided by the Supercomputer System, Human Genome Center, Institute of Medical Science, The University of Tokyo; and RIKEN Supercomputer system, RICC.  ... 
pmid:22230938 fatcat:plw5ias6wrfcpps7adfr6nb274

SupraBiology 2014: Promoting UK-China collaboration on Systems Biology and High Performance Computing

Ettore Murabito, Riccardo Colombo, Chengkun Wu, Malkhey Verma, Samrina Rehman, Jacky Snoep, Shao-Liang Peng, Naiyang Guan, Xiangke Liao, Hans V. Westerhoff
2015 Quantitative Biology  
Systems Biology in Education Computational Biology on the Tianhe-2 Supercomputer The report ends with a discussion section relating the ideas that have been pushed forward to establish collaborations  ...  In particular, the material hereby presented is organized around five main areas of interest: Systems Biology in medicine Computational methods of Systems Biology Computational Biology for Industry Computational  ...  DISCUSSION How can Systems Biology benefit from supercomputing?  ... 
doi:10.1007/s40484-015-0039-9 fatcat:qu4tcgwuhfbfveg55e2vlzmbvy

Multiscale Cancer Modeling and In Silico Oncology: Emerging Computational Frontiers in Basic and Translational Cancer Research

Georgios S Stamatakos, Norbert Graf
2013 Journal of Bioengineering and Biomedical Sciences  
Inferring gene and protein interaction networks: involves applying dimensionality reduction techniques such as principal component analysis, hierarchical clustering and tree constructions, differential  ...  Inferring network topologies: involves identification of interaction motifs such as feedback or feed forward loops, methods to infer bistability and robustness, construction and curation of Boolean networks  ...  Computational resources were available partly through US extreme science and engineering discovery environment (XSEDE) through a supercomputing resource allocation grant.  ... 
doi:10.4172/2155-9538.1000e114 pmid:30740263 pmcid:PMC6368085 fatcat:ybzcgmqeajerdbjrq34vp7tg3i

SWARM

Xinghua Shi, Rick Stevens
2008 Proceedings of the 6th international workshop on Challenges of large applications in distributed environments - CLADE '08  
to assemble the predictors, inferring on the ensemble of predictors to insert missing data, and eventually improving draft metabolic networks automatically.  ...  The availability of a large number of metabolic models will lead to a new generation of important biological hypotheses and experimental designs based on the analysis of these models.  ...  The authors greatly appreciate reviewers for their time and invaluable suggestions.  ... 
doi:10.1145/1383529.1383535 dblp:conf/clade/ShiS08 fatcat:ghefpn2brvb6hfiqbuufinaak4

Proceedings of the Seventh Annual UT-ORNL-KBRIN Bioinformatics Summit 2008

Eric C Rouchka, Julia Krushkal, Daniel Goldowitz
2008 BMC Bioinformatics  
putting together a well received scientific program.  ...  In addition, we wish to thank Bethany Coates, Stephanie Dearing, Terry Mark-Major, and Michelle Padgett for all of their efforts in putting together all of the details that allowed for the meeting to proceed  ...  The first module concentrated on using NCBI's resources for searching for gene-based information based on a RefSeq record, including sequence information such as reference gene, isoforms, single nucleotide  ... 
doi:10.1186/1471-2105-9-s7-i1 pmcid:PMC3313171 fatcat:dfq3og2q4zf3devanhvjon3gnu

Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer [article]

Mu Gao and Mark Coletti and Russell B. Davidson and Ryan Prout and Subil Abraham and Benjamin Hernandez and Ada Sedova
2022 arXiv   pre-print
Leadership-class computing resources can be used to perform genome-scale protein structure prediction using state-of-the-art deep learning models, providing a wealth of new data for systems biology applications  ...  equivalent to using the majority of the supercomputer for one hour.  ...  AlphaFold2 on the Summit Supercomputer using Singularity The computing power of the Summit supercomputer is an important resource for proteome-scale protein structure prediction; one of our aims is to  ... 
arXiv:2201.10024v1 fatcat:wvrpsig3jzfqphcc4o265iynhe

JUWELS Booster – A Supercomputer for Large-Scale AI Research [article]

Stefan Kesselheim, Andreas Herten, Kai Krajsek, Jan Ebert, Jenia Jitsev, Mehdi Cherti, Michael Langguth, Bing Gong, Scarlet Stadtler, Amirpasha Mozaffari, Gabriele Cavallaro, Rocco Sedona (+6 others)
2021 arXiv   pre-print
We exemplify its potential for research application by presenting large-scale AI research highlights from various scientific fields that require such a facility.  ...  With its system architecture, most importantly its large number of powerful Graphics Processing Units (GPUs) and its fast interconnect via InfiniBand, it is an ideal machine for large-scale Artificial  ...  Further computing time was provided on supercomputer JUSUF in frame of offer for epidemiology research on COVID-19 by JSC.  ... 
arXiv:2108.11976v1 fatcat:22wyf42eordsrekcutoadpujd4

Intracellular Signaling: Spatial and Temporal Control

Ion I. Moraru, Leslie M. Loew
2005 Physiology  
Computer simulations are an alternative way to achieve this goal-quite possibly the only way for complex systems.  ...  Cells integrate many inputs through complex networks of interacting signaling pathways.  ...  The first type of data is now readily obtainable for gene and protein expression on a large scale (microarrays and mass spectrometry techniques-genome, transcriptome, proteome), or, when necessary, complemented  ... 
doi:10.1152/physiol.00052.2004 pmid:15888574 fatcat:s5hpwmryhnhmxj6srl7avtjrum

It's the System, Stupid: How Systems Biology Is Transforming

2010 Biotechnology healthcare  
So far, little is known about systems biology and its potential for changing how we diagnose and treat disease.  ...  That will change soon, say the systems experts, who advise payers to begin learning now about how it could make healthcare efficient.  ...  "dynamic large-scale computer models of human disease."  ... 
pmid:22478806 pmcid:PMC2873723 fatcat:hio7smwadzayli6ht7ycjicsne

Editorial (Thematic Issue: Protein Systems Biology: Method, Regulation, and Network)

Qingfeng Chen, Ming Chen
2014 Current protein and peptide science  
ACKNOWLEDGEMENTS We wish to thank all the authors who have contributed with their work to foster the dissemination of scientific excellence in the protein network biology field; all the reviewers for giving  ...  their time and expertise to evaluate manuscripts submitted for this publication.  ...  In many ongoing studies, data-sharing has become a popular way for a large scale genomic or proteomic comparisons.  ... 
doi:10.2174/1389203715666140724091730 pmid:25135673 fatcat:liyexnkofndkhe2h3dzcpzfqli

ARACNe-AP: gene network reverse engineering through adaptive partitioning inference of mutual information

Alexander Lachmann, Federico M. Giorgi, Gonzalo Lopez, Andrea Califano
2016 Bioinformatics  
The accurate reconstruction of gene regulatory networks from large scale molecular profile datasets represents one of the grand challenges of Systems Biology.  ...  the Network inference accuracy of the original algorithm.  ...  Many computational approaches have been proposed for the reverse engineering of gene regulatory networks from large-scale gene expression profile data.  ... 
doi:10.1093/bioinformatics/btw216 pmid:27153652 pmcid:PMC4937200 fatcat:jcj47ofs2jhcdbdwhsjd7jyfei

Performance of distributed multiscale simulations

J. Borgdorff, M. Ben Belgacem, C. Bona-Casas, L. Fazendeiro, D. Groen, O. Hoenen, A. Mizeranschi, J. L. Suter, D. Coster, P. V. Coveney, W. Dubitzky, A. G. Hoekstra (+2 others)
2014 Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences  
A model to reverse-engineer gene-regulatory networks (MultiGrain) from the systems biology community [20] and an irrigation network model (Canals) from the hydrology community [29] .  ...  Such gene networks typically consist of dozens or hundreds of genes.  ... 
doi:10.1098/rsta.2013.0407 pmid:24982258 pmcid:PMC4084531 fatcat:p46v5saj3zealafus5flvrtuhi

SJARACNe: a scalable software tool for gene network reverse engineering from big data

Alireza Khatamian, Evan O Paull, Andrea Califano, Jiyang Yu, Jonathan Wren
2018 Bioinformatics  
Reverse engineering of biological networks from high-throughput gene expression profiles has been one of the grand challenges in systems biology.  ...  resources to efficiently construct complex regulatory and signaling networks from thousands of gene expression profiles.  ...  Rice, Manjunath Kustagi for code contributions, Jinghui Zhang and Michael Rusch for resource support and members in the Yu and Califano labs for testing and improving SJARACNe.  ... 
doi:10.1093/bioinformatics/bty907 pmid:30388204 pmcid:PMC6581437 fatcat:tj6v6idlg5e7xis65mamgb3q5y

Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms

Jack Y Yang, A Dunker, Jun S Liu, Xiang Qin, Hamid R Arabnia, William Yang, Andrzej Niemierko, Zhongxue Chen, Zuojie Luo, Liangjiang Wang, Yunlong Liu, Dong Xu (+3 others)
2014 BMC Bioinformatics  
In particular, advances in RNA-Seq technology has helped the studies of transcriptome, RNA expressed from the genome, while systems biology on the other hand provides more comprehensive pictures, from  ...  underlying mechanisms of gene regulations and networks.  ...  Declaration The funding for publication of the article has come from the MidSouth Bioinformatics Centre, and the Joint Bioinformatics Ph.  ... 
doi:10.1186/1471-2105-15-s17-i1 pmid:25559210 pmcid:PMC4304187 fatcat:3nwwbbbce5grjbmf22cltwc7oa
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