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Peer-reviewed Publications

(in reverse chronological order)

*All these material are presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.


(2018 and preprints)

miniVite: A graph analytics benchmarking tool for massively parallel systems. 
S. Ghosh, M. Halappanavar, A. Tumeo, A. Kalyanaraman, A. Gebremedhin. 
Proc. IEEE International Workshop on Performance Modeling, Benchmarking and Simulation (PMBS'18), held in conjunction with ACM/IEEE Supercomputing (SC'18), Accepted, 2018.

Scalable distributed memory community detection using Vite. 
S. Ghosh, M. Halappanavar, A. Tumeo, A. Kalyanaraman, A. Gebremedhin. 
Proc. IEEE High Performance Extreme Computing (HPEC'18), Accepted, 2018.
2018 IEEE HPEC/MIT Graph Challenge: Innovation Award winner.
preprint

Detecting divergent subpopulations in phenomics data using interesting flares.
M. Kamruzzaman, A. Kalyanaraman, B. Krishnamoorthy.
Proc. ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), pp. 155-164, 2018.
PDF

Exploiting intra-type information in bipartite community detection.
Paola Pesantez-Cabrera, Ananth Kalyanaraman and Mahantesh Halappanavar.
Proc. SIAM Network Science workshop, (accepted as a short paper), p.2, 2018.
preprint

Alignment-free clustering of large data sets of unannotated protein conserved regions Using MinHashing.
A. Abnousi, S.L. Broschat, A. Kalyanaraman.
BMC Bioinformatics, vol. 19, no. 1, p. 83, 2018.
doi: 10.1186/s12859-18-2080-y
PDF

Distributed Louvain algorithm for graph community detection.
S. Ghosh, M. Halappanavar, A. Tumeo, A. Kalyanaraman, H. Lu, D. Chavarria-Miranda, A. Khan, A. Gebremedhin.
Proc. IEEE International Parallel and Distributed Processing Symposium (IPDPS)
, pp. 885-895, 2018.
PDF

Interesting paths in the Mapper.
A. Kalyanaraman, M. Kamruzzaman, B. Krishnamoorthy.
arXiV preprint arXiv:1712.10197, 2017.
preprint

Toward a scalable framework for complex high-dimensional phenomics data.
M. Kamruzzaman, A. Kalyanaraman, B. Krishnamoorthy, P.S. Schnable.
arXiV  preprint arXiv:1707.04362, 2017.
preprint

Efficient detection of communities in biological bipartite networks.
P. Pesantez, A. Kalyanaraman.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Accepted/In Press, 2017.
doi:
10.1109/TCBB.2017.2765319
preprint

FastEtch: A fast sketch-based assembler for genomes.
P.Ghosh, A. Kalyanaraman.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), In Press, 2017.
doi:
10.1109/TCBB.2017.2737999
preprint

(2017)

Approximate computing techniques for iterative graph algorithms.
A. Panyala, O. Subasi, M. Halappanavar, A. Kalyanaraman, D. Chavarria-Miranda, S. Krishnamoorthy.
Proc. IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC'17), pp.23-32, 2017.
doi: 10.1109/HiPC.2017.00013
PDF

Scalable static and dynamic community detection using Grappolo.
M. Halappanavar, H. Lu, A. Kalyanaraman, A. Tumeo.
2017 IEEE HPEC/DARPA/MIT Graph Challenge Champion.
Proc. IEEE High Performance Extreme Computing (HPEC'17), pp. 1-6, 2017.
PDF

Accelerating Graph Community Detection with Approximate Updates via an Energy-Efficient NoC.
K. Duraisamy, H. Lu, P. Pande, A. Kalyanaraman.
Proc. Design Automation Conference (DAC), p.89, June 18-22, 2017.
doi: 10.1145/3061639.3062194.
PDF

Algorithms for Balanced Colorings with Applications in Parallel Computing.
H. Lu, M. Halappanavar, D. Chavarria-Miranda, A. Gebremedhin, A. Panyala, A. Kalyanaraman.
IEEE Transactions on Parallel and Distributed Systems, vol. 28, no. 5, pp. 1240-1256, May 1 2017.
doi: 10.1109/TPDS.2016,2620142.
PDF

(2016)

A Fast Alignment-Free Approach for de novo Detection of Protein Conserved Regions. 
A. Abnousi, S.L. Broschat, A. Kalyanaraman.
PLOS ONE, 11(8), p.e0161338, 2016.
doi: 10.1371/journal.pone.0161338.
PDF

Detecting Communities in Biological Bipartite Networks. 
P. Pesantez, A. Kalyanaraman.
Proc. ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB)
, pp. 98-107, 2016.
doi: 10.1145/2975167.2975177.
PDF

A Fast Sketch-based Assembler for Genomes.
P. Ghosh, A. Kalyanaraman.
Proc. ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB)
, pp. 241-250, 2016. Best Student Paper Award.
doi: 10.1145/2975167.2975192.
PDF

Characterizing the Role of Environment on Phenotypic Traits using Topological Data Analytics. 
M. Kamruzzaman, A. Kalyanaraman, B. Krishnamoorthy.
Proc. ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), pp. 487-488, 2016.
doi: 10.1145/2975167.2985646.
PDF

High performance and energy efficient Network-on-Chip architectures for graph analytics.
K. Duraisamy, H. Lu, P. Pande, A. Kalyanaraman.
ACM Transactions on Embedded Computing Systems (TECS), vol. 15, no. 4, p. 66, 2016.
doi: 10.1145/2961027.
PDF

On the Impact of Widening Vector Registers on Sequence Alignment.
J. Daily, A. Kalyanaraman, S. Krishnamoorthy, B. Ren. 
Proc. International Conference on Parallel Processing, pp. 506-515, 2016.
PDF

CisSERS: Cutomizable in silico Sequence Evaluation for Restriction Sites.
R. Sharpe, T. Koepke, A. Harper, J. Grimes, M. Galli, M. Satoh-Cruz, A. Kalyanaraman, K. Evans, D. Kramer, A. Dhingra.
PLOS ONE, 11(4):e0152404, 2016.
doi: 10.1371/journal.pone.015404.
PDF

Fast uncovering of graph communities on a chip: Toward scalable community detection on multicore and manycore platforms.
A. Kalyanaraman, M. Halappanavar, D. Chavarria-Miranda, H. Lu, K. Duraisamy, P. Pande.
Foundations and Trends in Electronic Design Automation (FnTEDA), Paperback 118 pages. now Publishers, ISBN-10: 1680831321, ISBN-13: 978-1680831320, 2016.
Online access

Fast SVD computations for synchrophasor algorithms.
T. Wu, S.A.N. Sarmadi, V. Venkatasubramanian, A. Pothen, A. Kalyanaraman.
IEEE Transactions on Power Systems, 31(2):1651-1652, 2016. 
doi: 10.1109/TPWRS.2015.2412679
Online access

(2015)

High performance and energy efficient wireless NoC-enabled multicore architecture for graph analytics.
K. Duraisamy, H. Lu, P. Pande, A. Kalyanaraman.
Proc. International Conference on Compilers, Architectures and Synthesis of Embedded Systems (CASES), pp. 147-156, 2015. Best Paper Finalist.
PDF

An alignment-free approach to cluster proteins using frequency of conserved k-mers.
A. Abnousi, S.L. Broschat, A. Kalyanaraman.
Proc. ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB), pp. 597-606, 2015.
doi: 10.1145/2808719.2812223
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On-Chip Network-Enabled Many-Core Architectures for Computational Biology Applications.
T. Majumder, P. Pande, A. Kalyanaraman.
Proc. Design, Automation and Test in Europe (DATE), 2015, pp. 259-264.
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Parallel heuristics for scalable community detection. 
H. Lu, M. Halappanavar, A. Kalyanaraman.
Parallel Computing, vol. 47, pp. 19-37, 2015.
doi: 10.1016/j.parco.2015.03.003
Online access

Balanced coloring for parallel computing applications.
H. Lu, M. Halappanavar, D. Chavarria, A. Gebremedhin, A. Kalyanaraman.
Proc. IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 7-16, 2015.
doi: 10.1109/IPDPS.2015/113. 
PDF

A work stealing based approach for enabling scalable optimal sequence homology detection.
J. Daily, A. Kalyanaraman, S. Krishnamoorthy, A. Vishnu.
Journal of Distributed and Parallel Computing (JPDC), Vol. 79-80, pp. 132-142, May 2015.
doi: 10.1016/j.jpdc.2014.08.009.
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(2014)

Scaling graph community detection on the Tilera Many-core architecture.
D. Chavarria, M. Halappanavar, A. Kalyanaraman.
Proc. IEEE International Conference on High Performance Computing (HiPC), December 17-20, 2014, Goa, India. 11 pages.
doi: 10.1109/HiPC.2014.7116708
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BioEarth: Envisioning and developing a new regional earth system model to inform natural and agricultural resource management.
J. Adam et al.
Climatic Change, pp. 1-17, 2014. 
doi: 10.1007/s10584-014-1115-2
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Parallel heuristics for scalable community detection.
H. Lu, M. Halappanavar, A. Kalyanaraman, S. Choudhury.
Proc. International Workshop on Multithreaded Architectures and Applications (MTAAP), IPDPS Workshops, pp. 1375-1385, 2014. 
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Design and implementation of Kepler workflows for BioEarth.
T. Mullis, M. Liu, A. Kalyanaraman, J. Vaughan, C. Tague, J. Adam.
Proc. 2014 International Conference on Computational Science (ICCS), Procedia Computer Science, vol. 29, pp. 1722-1732, 2014.
doi: 10.1016/j.procs.2014.05.157
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Hardware Accelerators in Computational Biology: Application, Potential and Challenges.
T. Majumder, P.P. Pande, A. Kalyanaraman. IEEE Design and Test of Computers: Special Issue on Hardware Acceleration, 31(1):8-18, 2014.
doi: 10.1109/MDAT.2013.2290118.
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Parallel algorithms for clustering biological graphs on distributed and shared memory architectures.
I. Rytsareva, T. Chapman, and A. Kalyanaraman.
International Journal of High Performance Computing and Networking: Special issue on Architectures and Algorithms for Irregular Applications (IJHPCN), 7(4):241-257, 2014.
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Wireless NoC platforms with dynamic task allocation for maximum likelihood phylogeny reconstruction.
T. Majumder, P.P. Pande, A. Kalyanaraman.
IEEE Design and Test of Computers, 31(3):54-64, 2014.
doi: 10.1109/MDAT.2013.2288778
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(2013)

Computational challenges in stability monitoring of power systems using large number of PMUs.
M.V. Venkatasubramanian, A. Pothen, A. Kalyanaraman, D.J. Sobajic.
Proc. National Workshop on Energy Cyber-physical Systems, organized by NSF, Arlington, VA, pp.1-3, 2013.

Empirical analysis of space-filling curves for scientific computing applications.
D. Deford, A. Kalyanaraman.
Proc. International Conference on Parallel Processing (ICPP), Lyon, France, pp. 170-179, 2013.
doi: 10.1109/ICPP.2013.26
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Scalable heuristics for clustering biological graphs.
I. Rytsareva, A. Kalyanaraman, K. Konwar, S. Hallam.
Proc. IEEE International Conference on Computational Advances in Bio and Medical Sciences (ICCABS), pp. 1-6, 2013.
doi: 10.1109/ICCABS.2013.6629214
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On clustering heterogeneous networks.
F. Poursabzi, A. Kalyanaraman.
Proc. SIAM Workshop on Network Science (NetSci13), (held in conjunction with 2013 SIAM Annual Meeting), San Diego, pp.1-2, 2013.
preprint


Network-on-chip with long-range wireless links for high-throughput scientific computation.
T. Majumder, P.P. Pande, A. Kalyanaraman.
Proc. 3rd Workshop on Communication Architecture for Scalable Systems (CASS’13), held in conjunction with IPDPS'13, pp. 781-790, 2013.
doi: 10.1109/IPDPSW.2013.72
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GPU-accelerated protein family identification for metagenomics.
C. Wu, A. Kalyanaraman.
Proc. 12th IEEE International Workshop on High Performance Computational Biology (HiCOMB’11), held in conjunction with IPDPS'13, pp. 559-568, 2013. (invited paper).
doi:10.1109/IPDPSW.2013.185
PDF

Comparison of clustering algorithms: An example with proteomic data.
N. Dasgupta, Y. Chen, A. Kalyanaraman, S. Daoud.
Advances and Applications in Statistics, 33(1):p63, 2013.
Online access

High-throughput, energy-efficient network-on-chip-based hardware accelerators.
T. Majumder, P.P. Pande, A. Kalyanaraman.
Sustainable Computing: Informatics and Systems (SUSCOM), 3(1):36-46, 2013.
doi: 10.1016/j.suscom.2013.01.001.
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(2012)

Towards Scalable Optimal Sequence Homology Detection.
J. Daily, S. Krishnamoorthy, and A. Kalyanaraman.
Proc. Workshop on Parallel Algorithms and Software for Analysis of Massive Graphs (ParGraph'12), pp.1-8, 2012.
doi: 10.1109/HiPC.2012.6507523
PDF

Evaluating socio-technical coordination in open-source communities: A cluster-based approach.
I. Rytsareva, Q. Le, E. Conner, A. Kalyanaraman, J. Panchal.
Proc. ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE), pp.2777-286, 2012.
doi: 10.1115/DETC2012-70604
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On-Chip network-enabled multi-core platforms targeting maximum likelihood phylogeny reconstruction.
T. Majumder, M. Borgens, P.P. Pande, A. Kalyanaraman.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 31(7):1061-1073, 2012.
doi:  10.1109/TCAD.2012.2188401
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pGraph: Efficient parallel construction of large-scale protein sequence homology graphs.
C. Wu, A. Kalyanaraman, W.R. Cannon.
IEEE Transactions on Parallel and Distributed Systems (TPDS), 23(10):1923-1933, 2012.
doi: 10.1109/TPDS.2012.19
PDF (suppl. material available on publisher's website)

Proteotyping of microbial communities using high performance optimization of proteome-spectra matches.
A. Hugo, D.J. Baxter, W.R. Cannon, A. Kalyanaraman, G. Kulkarni, S.J. Callister.
Proc. Pacific Symposium on Biocomputing (PSB)
, 2012.
doi: 10.1142/9789814366496_0022
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NoC-based hardware accelerator for breakpoint phylogeny.
T. Majumder, P. Pande, A. Kalyanaraman.
IEEE Transactions on Computers, 2012, 61(6):857-869.
doi: 10.1109/TC.2011.100
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(2011)

An efficient MapReduce algorithm for parallelizing large-scale graph clustering.
I. Rytsareva, A. Kalyanaraman.
ParGraph - Workshop on Parallel Algorithms and Software for Analysis of Massive Graphs, Held in conjunction with HiPC'11, India, p.1-9, 2011.
PDF

An OpenMP algorithm and implementation for clustering biological graphs.
T. Chapman, A. Kalyanaraman.
IA3 - Workshop on Irregular Applications: Architectures & Algorithms (Held in conjunction with SC'11), Seattle, WA, pp. 3-10, 2011. 
doi: 10.1145/2089142.2089146
PDF

MapReduce implementation of a hybrid spectral library-database search method for large-scale peptide identification.
A. Kalyanaraman, W.R. Cannon, B. Latt, D.J. Baxter.
Bioinformatics, 2011, 27(21):3072-3073.
doi:10.1093/bioinformatics/btr523.
PDF (suppl. material available on publisher's website)

Accelerating Maximum Likelihood based phylogenetic kernels using Network-on-chip.
T. Majumder, P. Pande, A. Kalyanaraman.
Proc. International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), pp. 17-24, 2011.
doi: 10.1109/SBAC-PAD.2011.17
PDF

Attenuation of virulence in an Apicomplexan hemoparasite results in reduced genomic diversity at the population level.
A.O.T. Lau, A. Kalyanaraman, I. Echaide, G.H. Palmer, R. Bock, M.J. Pedroni, M. Rameshkumar, M.B. Ferreira, T.I. Fletcher, T.F. McElwain.
BMC Genomics. 12:410, 2011.
doi:10.1186/1471-2164-12-410
PDF

Genome assembly.
A. Kalyanaraman.
Encyclopedia of Parallel Computing, D. Padua (ed.), Springer Science+Business Media LLC, pp. 755-768, 2011.
doi: 10.1007/978-0-387-09766-4
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(2010)

The genome of the domesticated apple (Malus domestica Borkh.).
R. Velasco, A. Zharkikh, J. Affourtit, A. Dhingra, A. Cestaro, A. Kalyanaraman, P. Fontana et al. (expanded author list)
Nature Genetics, 42:833-839, 2010.
doi:10:1038/ng.654 
PDF

A scalable parallel algorithm for large-scale protein sequence homology detection.
C. Wu, A. Kalyanaraman, W. Cannon.
Proc. International Conference on Parallel Processing (ICPP), 2010, pp. 333-342.
doi: 10.1109/ICPP.2010.41
PDF

An optimized NoC architecture for accelerating TSP kernels in breakpoint median problem.
T. Majumder, S. Sarkar, P. Pande, A. Kalyanaraman.
Proc. IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP), pp. 89-96, 2010.
doi: 10.1109/ASAP.2010.5540797
PDF

Hardware accelerators for biocomputing: A survey.
S. Sarkar, T. Majumder, A. Kalyanaraman, P. Pande.
Proc. IEEE International Symposium on Circuits and Systems (ISCAS), pp. 3789-3792, 2010.
doi: 10.1109/ISCAS.2010.5537736
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Genome sequencing and analysis of the model grass Brachypodium distachyon.
The International Brachypodium Initiative. Nature, 463, 763-768, 2010.
(
expanded author list)
doi:10.1038/nature08747
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Network-on-chip hardware accelerators for biological sequence alignments.
S. Sarkar, G. Kulkarni, P. Pande, A. Kalyanaraman.
IEEE Transactions on Computers, 59(1):29-41, 2010.
doi: 10.1109/TC.2009.133
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(2009)

Using clouds for for data-intensive computing in proteomics.
A. Kalyanaraman, D. Baxter, W. Cannon.
Proc. Workshop on Using Clouds for Parallel Computations in Systems Biology, held in conjunction with SC|09, Portland, OR, November 16, 2009.
PDF

The B73 Maize Genome: Complexity, diversity and dynamics.
P.S. Schnable et al. (expanded author list)
Science, 326(5956):1112-1115, 2009.
doi: 10.1126/science.1178534
PDF

Detailed analysis of a contiguous 22-Mb region of the maize genome.
F. Wei et al. (expanded author list)
PLoS Genetics
, 5(11):e1000728, 2009.
doi:10.1371/journal.pgen.1000728
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DNAjig: A new approach for building DNA nanostructures.
Md. Muksitul Haque, A. Kalyanaraman, A. Dhingra, N. Abu-lail, K. Graybeal.
Proc. IEEE International Conference on Bioinformatics & Biomedicine (BIBM), Washington D.C., November 1-4, pp. 379-383, 2009.
doi: 10.1109/BIBM.2009.71
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A scalable parallel approach for peptide identification from large-scale mass spectrometry data.
G. Kulkarni, A. Kalyanaraman, W. Cannon, D. Baxter.
Proc. International Conference on Parallel Processing Workshops (ICPP-W), pp. 423-430, September 22-25, 2009.
doi: 10.1109/ICPPW.2009.41
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(2008)

An efficient parallel approach for identifying protein families in large-scale metagenomic data sets.
C. Wu, A. Kalyanaraman.
Proc. ACM/IEEE conference on Supercomputing (SC|08), Austin, TX, November 15-21, pp. 1-10, 2008, ISBN 978-1-4244-2835-9, IEEE Press, Piscataway, NJ, USA.
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An information theoretic approach for the discovery of irregular and repetitive patterns in genomic data.
W. Davis, A. Kalyanaraman, D. Cook.
Proc. IEEE Computational Intelligence in Bioinformatics and Bioengineering (CIBCB'08), Sun Valley, ID, September 15-17, 2008.
doi: 10.1109/CIBCB.2008.4675756
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(2007)

Assembling genomes on large-scale parallel computers.
A. Kalyanaraman, S.J. Emrich, P.S. Schnable, S. Aluru.
Journal of Parallel and Distributed Computing (JPDC), 67(12):1240-1255, 2007.
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Massively parallel clustering of Expressed Sequence Tags.
S.J. Emrich, A. Kalyanaraman, S. Aluru.
Proc. ISCA 20th International Conference on Parallel and Distributed Computing Systems (PDCS'07), Las Vegas, NV,  September 24-26, 2007.
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(2006)

Efficient algorithms and software for detection of full-length LTR retrotransposons.
A. Kalyanaraman, S. Aluru. Journal of Bioinformatics and Computational Biology (JBCB), 4(2):197-216, 2006.
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Turning repeats to advantage: Scaffolding genomic contigs using LTR retrotransposons.
A. Kalyanaraman, S. Aluru, P.S. Schnable.
Proc. LSS Computational Systems Bioinformatics (CSB'06), 167-178, 2006.
PDF

Assembling genomes on large-scale parallel computers.
A. Kalyanaraman, S.J. Emrich, P.S. Schnable, S. Aluru.
Proc. IEEE International Parallel and Distributed Processing Symposium (IPDPS'06), 2006. (Best Paper Award)
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(2005 or earlier)

Efficient algorithms and software for detection of full-length LTR retrotransposons.
A. Kalyanaraman, S. Aluru.
IEEE Computational Systems Bioinformatics Conference (CSB'05), pp. 56-64, 2005. (Best Paper Award)
PDF

Expressed Sequence Tags: Clustering and applications.
A. Kalyanaraman, S. Aluru.
In
Handbook of Computational Molecular Biology, Edited by S. Aluru, Chapman & Hall/CRC Computer and Information Science Series, 2005.

Algorithms for large-scale clustering and assembly of biological sequence data.
S. Emrich, A. Kalyanaraman, S. Aluru.
In
Handbook of Computational Molecular Biology, Edited by S. Aluru, Chapman & Hall/CRC Computer and Information Science Series, 2005.

A survey of SL1-spliced transcripts from the root-lesion nematode Pratylenchus penetrans.
M. Mitreva, A.A. Elling, M. Dante, A.P. Kloek, A. Kalyanaraman, S. Aluru, S.W. Clifton, D.M. Bird, T.J. Baum, J.P. McCarter.
Molecular Genetics and Genomics (MGG), 272:138-148, 2004.
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Space-conserving optimal DNA-protein alignment.
P. Ko, M. Narayanan, A. Kalyanaraman, S. Aluru.
Proc. IEEE Computational Systems Bioinformatics Conference (CSB'04), pp. 77-85, 2004.
PDF

Space and time efficient parallel algorithms and software for EST clustering. 
A. Kalyanaraman, S. Aluru, V. Brendel, S. Kothari.
IEEE Transactions on Parallel and Distributed Systems (TPDS), 14(12):1209-1221, 2003.
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Efficient clustering of large EST data sets on parallel computers.
A. Kalyanaraman, S. Aluru, S. Kothari, V. Brendel.
Nucleic Acids Research (NAR), 31(11):2963-2974, 2003.
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Space and time efficient parallel algorithms and software for EST clustering.
A. Kalyanaraman, S. Aluru, S. Kothari.
Proc. International Conference on Parallel Processing (ICPP'02), 331-339, 2002.
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Parallel EST clustering.
A. Kalyanaraman, S. Aluru, S. Kothari.
Proc. First International Workshop on High Performance Computational Biology (HiCOMB'02), held in conjunction with IPDPS '02, 2002.
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Ph.D. DISSERTATION

Title:    Large-scale methods in computational genomics
Graduation date:    Summer 2006
Advisor:    Prof. Srinivas Aluru
Institution:    Iowa State University
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