Discovering biological knowledge by integrating high-throughput data and scientific literature on the cloud

Concurrency and Computation: Practice and Experience

Volumn 26, Issue 10, 2014, Pages 1771-1786

  Spampinato, C ^a   Kavasidis, I ^a   Aldinucci, M ^b   Pino, C ^a   Giordano, D ^a   Faro, A ^a  

^a UNIVERSITY OF CATANIA   (Italy)

^b UNIVERSITY OF TURIN   (Italy)

Author keywords

bioinformatics; knowledge discovery; text mining

Indexed keywords

BIOINFORMATICS; DATA MINING; GENES; RNA; TEXT MINING;

ANNOTATED DATABASE; BIOLOGICAL ENTITIES; BIOLOGICAL HYPOTHESIS; DATA-INTENSIVE APPLICATION; GENE-DISEASE ASSOCIATIONS; HIGH-THROUGHPUT DATA; KNOWLEDGE DISCOVERY SYSTEMS; SCIENTIFIC LITERATURE;

INFRASTRUCTURE AS A SERVICE (IAAS);

EID: 84902532512     PISSN: 15320626     EISSN: 15320634     Source Type: Journal    
DOI: 10.1002/cpe.3130     Document Type: Article

References (61)

1. Özgür A, Vu T, Erkan G, Radev D,. Identifying gene-disease associations using centrality on a literature mined gene-interaction network. Bioinformatics 2008; 24 (13): i277-i285.
2. Ananiadou S, Kell DB, Tsujii Ji,. Text mining and its potential applications in systems biology. Trends in Biotechnology 2006; 24 (12): 571-579. DOI: 10.1016/j.tibtech.2006.10.002.
3. Jensen LJ, Saric J, Bork P,. Literature mining for the biologist: from information retrieval to biological discovery. Nature Reviews Genetics 2006; 7 (2): 119-129.
4. Liu Y, Navathe S, Civera J, Dasigi V, Ram A, Ciliax B, Dingledine R,. Text mining biomedical literature for discovering gene-to-gene relationships: a comparative study of algorithms. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2005; 2 (1): 62-76.
5. Von Mering C, Jensen L, Snel B, Hooper S, Krupp M, Foglierini M, Jouffre N, Huynen M, Bork P,. String: known and predicted protein-protein associations, integrated and transferred across organisms. Nucleic Acids Research 2005; 33 (suppl 1): D433-D437.
6. Faro A, Giordano D, Spampinato C,. Combining literature text mining with microarray data: advances for system biology modeling. Briefings in Bioinformatics 2012; 13: 61-82.
7. Ekins S, Nikolsky Y, Bugrim A, Kirillov E, Nikolskaya T,. Pathway mapping tools for analysis of high content data. Methods in Molecular Biology (Clifton, N.J.) 2007; 356: 319-350.
8. Wu J, Mao X, Cai T, Luo J, Wei L,. KOBAS server: a web-based platform for automated annotation and pathway identification. Nucleic Acids Research 2006; 34: W720-724.
9. Frijters R, Heupers B, van Beek P, Bouwhuis M, van Schaik R, de Vlieg J, Polman J, Alkema W,. CoPub: a literature-based keyword enrichment tool for microarray data analysis. Nucleic Acids Research 2008; 36: W406-410.
10. Tranchevent L, Barriot R, Yu S, Van Vooren S, Van Loo P, Coessens B, De Moor B, Aerts S, Moreau Y,. Endeavour update: a web resource for gene prioritization in multiple species. Nucleic Acids Research 2008; 36 (suppl 2): W377-W384.
11. Perez-Iratxeta C, Wjst M, Bork P, Andrade MA,. G2D: a tool for mining genes associated with disease. BMC Genetics 2005; 6 (1): 1-9.
12. Spampinato C, Giordano D, Kavasidis I, Milardo S,. Biowizard: Discovering and validating associations between biological entities by integrated analysis of scientific literature and experimental data. 2012 25th International Symposium on Computer-based medical systems (CBMS), IEEE, Rome, Italy, 20-22 June 2012; 1-6.
13. Mell P, Grance T,. The NIST definition of cloud computing. NIST Special Publication 2011; 800: 1-3.
14. Bateman A, Wood M,. Cloud computing. Bioinformatics 2009; 25 (12): 1475-1475.
15. Dai L, Gao X, Guo Y, Xiao J, Zhang Z,. Bioinformatics clouds for big data manipulation. Biology Direct 2012; 7 (1): 1-7.
16. Hey A, Tansley S, Tolle K,. The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research Redmond: WA, 2009.
17. Li H, Durbin R,. Fast and accurate short read alignment with burrows-wheeler transform. Bioinformatics 2009; 25 (14): 1754-1760.
18. Schatz M,. Cloudburst: highly sensitive read mapping with MapReduce. Bioinformatics 2009; 25 (11): 1363-1369.
19. Shendure J, Ji H,. Next-generation dna sequencing. Nature Biotechnology 2008; 26 (10): 1135-1145.
20. Matsunaga A, Tsugawa M, Fortes J,. Cloudblast: combining MapReduce and virtualization on distributed resources for bioinformatics applications. IEEE Fourth International Conference on Escience, 2008. eScience'08, IEEE, Indianapolis, Indiana, USA, 7-12 December 2008; 222-229.
21. Johnson M, Zaretskaya I, Raytselis Y, Merezhuk Y, McGinnis S, Madden T,. NCBI blast: a better web interface. Nucleic Acids Research 2008; 36 (suppl 2): W5-W9.
22. Stein L,. The case for cloud computing in genome informatics. Genome Biology 2010; 11 (5): 207.
23. Li H, Homer N,. A survey of sequence alignment algorithms for next-generation sequencing. Briefings in Bioinformatics 2010; 11 (5): 473-483.
24. Grossman R, Gu Y,. Data mining using high performance data clouds: experimental studies using sector and sphere. Proceeding of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, Las Vegas, NV, USA, 24-27 August 2008; 920-927.
25. Aldinucci M, Torquati M, Spampinato C, Drocco M, Misale C, Calcagno C, Coppo M,. Parallel stochastic systems biology in the cloud. Briefings in Bioinformatics 2013. DOI: 10.1093/bib/bbt040.
26. Sun X, Fan L, Yan L, Kong L, Ding Y, Guo C, Sun W,. Deliver bioinformatics services in public cloud: challenges and research framework. 2011 IEEE 8th International Conference on E-Business Engineering (ICEBE), Beijing, China, 19-21 October 2011; 352-357.
27. Dean J, Ghemawat S,. MapReduce: simplified data processing on large clusters. Communications of the ACM 2008; 51 (1): 107-113. DOI: 10.1145/1327452.1327492.
28. Shvachko K, Kuang H, Radia S, Chansler R,. The hadoop distributed file system. Proceedings of the 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST) (MSST '10), 2010; 1-10.
29. Thusoo A, Sarma J, Jain N, Shao Z, Chakka P, Anthony S, Liu H, Wyckoff P, Murthy R,. Hive: a warehousing solution over a map-Reduce framework. Proceedings of the VLDB Endowment 2009; 2 (2): 1626-1629.
30. Liu H, Orban D,. Cloud MapReduce: a MapReduce implementation on top of a cloud operating system. 2011 11th IEEE/ACM International Symposium on Cluster, cloud and Grid Computing (CCGrid), IEEE, Newport Beach, CA, USA, 2011; 464-474.
31. Dean J, Ghemawat S,. MapReduce: simplified data processing on large clusters. Communications of the ACM 2008; 51 (1): 107-113.
32. Watson P, Leahy D, Hiden H, Woodman S, BerryLiu J,. An azure science cloud for drug discovery. Microsoft External Research Symposium, Redmond, Washington, USA, 30-31 March 2009.
33. Ekanayake J, Gunarathne T, Qiu J,. Cloud technologies for bioinformatics applications. IEEE Transactions on Parallel and Distributed Systems 2011; 22 (6): 998-1011.
34. Adams MD, Kelley JM, Gocayne JD, Dubnick M, Polymeropoulos MH, Xiao H, Merril CR, Wu A, Olde B, Moreno RF,. Complementary DNA sequencing: expressed sequence tags and human genome project. Science 1991; 252 (5013): 1651-1656.
35. Häsler J, Strub K,. Alu elements as regulators of gene expression. Nucleic Acids Research 2006; 34 (19): 5491-5497.
36. Nazareno F, Lee K, Cho W,. Mining molecular interactions from scientific literature using cloud computing. 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), IEEE, Hong Kong, China, 18-21 December 2010; 864-865.
37. Lin J, Dyer C,. Data-intensive text processing with MapReduce. Synthesis Lectures on Human Language Technologies 2010; 3 (1): 1-177.
38. Langmead B, Schatz M, Lin J, Pop M, Salzberg S,. Searching for SNPS with cloud computing. Genome Biology 2009; 10 (11): 1-10.
39. Contrail project home page (Contrail: Assembly of Large Genomes using Cloud Computing). http://sourceforge.net/apps/mediawiki/contrail-bio/index.php? title=Contrail.
40. Langmead B, Hansen K, Leek J,. Cloud-scale RNA-sequencing differential expression analysis with Myrna. Genome Biology 2010; 11 (8): 1-11.
41. Rezaul K, Golam B, Jeong B, Choi HJ,. Cloud technology for mining association rules in microarray gene expression datasets. International Journal of Database Theory & Application 2012; 5 (2): 61-74.
42. Delmerico J, Byres N, Brunn A, Jones M, Gall S, Chandlery V,. Comparing the performance of clusters, Hadoop, and Active Disks on microarray correlation computations. 2009 International Conference on High Performance Computing (HIPS), IEEE, 2009; 378-387.
43. Nguyen T, Shi W, Ruden D,. CloudAligner: A fast and full-featured MapReduce based tool for sequence mapping. BMC Research Notes 2011; 4:171, pp. 1-7.
44. Splanchnomega K, Vera K, Sheath A, Miller J,. Adding semantics to web services standards. Proceedings of the International Conference on Web Services, New York: USA, 2003; 395-401.
45. Roman D, Killer U, Clause H, de Bruin J, Larva R, Stroller M, Pollers A, Fever C, Bustler C, Fennel D,. Web service modeling ontology. Applied Ontology 2005; 1 (1): 77-106.
46. Fusaro VA, Patil P, Gafni E, Wall DP, Tonellato PJ,. Biomedical cloud computing with Amazon Web Services. PLoS Computational Biology 2011; 7 (8): 1-6.
47. Krampis1 K, Booth T, Chapman B, Tiwari B, Bicak M, Field D, Nelson K,. Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community. BMC Bioinformatics 2012; 13:42, pp. 1-8.
48. Angiuoli SV, Matalka M, Gussman A, Galens K, Vangala M, Riley D, Arze D, White J, White O, Fricke W,. CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing. BMC Bioinformatics 2011; 12:356, pp. 1-15.
49. Angiuoli S, White J, Matalka M, White O, Fricke W,. Resources and costs for microbial sequence analysis evaluated using virtual machines and cloud computing. PLoS ONE 6 (10): 1-10.
50. Dudley J, Pouliot Y, Chen R, Morgan A, Butte A,. Translational bioinformatics in the cloud: an affordable alternative. Genome Medicine 2010; 2:51, pp. 1-6.
51. Maggot D, Osteal J, Spruit KD, Tractus T,. Entrez gene: gene-centered information at NCBI. Nucleic Acids Research 2005; 33 (suppl 1): D54-D58.
52. Liposome CE,. Medical subject headings (mesh). Bulletin of the Medical Library Association 2000; 88 (3): 265.
53. Griffith-Jones S, Saint HK, Van Dongle S, Unright AJ,. miRBase: tools for microns genomics. Nucleic Acids Research 2008; 36 (suppl 1): D154-D158.
54. Cunningham H, Maynard D, Bontcheva K,. Text Processing with GATE. Gateway Press CA, 2011.
55. Settles B,. ABNER: an open source tool for automatically tagging genes, proteins and other entity names in text. Bioinformatics 2005; 21 (14): 3191-3192.
56. Huang DW, Sherman BT, Tan Q, Kir J, Liu D, Bryant D, Guo Y, Stephens R, Baseler MW, Lane HC, Lempicki RA,. David bioinformatics resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Research 2007; 35 (suppl 2): W169-W175.
57. Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J,. TM4: a free, open-source system for microarray data management and analysis. Biotechnology 2003; 34: 374-378.
58. Ben-Don A, Shammer R, Yakking Z,. Clustering gene expression patterns. Journal of Computational Biology 1999; 6 (3/4): 281-297.
59. Antigen-Yield M, Prate W,. A new evaluation methodology for literature-based discovery systems. Journal of Biomedical Informatics 2009; 42: 633-643.
60. Gob K, Carsick M, Vale D, Chills B, Vidual M, Barbásci A,. The human disease network. Proceedings of the National Academy of Sciences 2007; 104 (21): 8685-8690.
61. Giordano D, Kavasidis I, Pino C, Spampinato C,. A semantic-based and adaptive architecture for automatic multimedia retrieval composition. 2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI), Madrid, Spain, 13-15 June 2011; 181-186.