Abstract
| Original language | English |
|---|---|
| Journal | BMC Bioinform. |
| Volume | 20 |
| DOIs | |
| Publication status | Published - 2019 |
Keywords
- Network tools
- Oral communication
- Personalised medicines
- Scientific contributions
- bioinformatics
- biology
- publication
- review
- genetics
- genomics
- health care delivery
- human
- Italy
- neoplasm
- personalized medicine
- procedures
- Computational Biology
- Delivery of Health Care
- Genomics
- Humans
- Neoplasms
- Precision Medicine
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The 2017 Network Tools and Applications in Biology (NETTAB) workshop: Aims, topics and outcomes : BMC Bioinformatics. / Romano, P.; Céol, A.; Dräger, A.; Fiannaca, A.; Giugno, R.; La Rosa, M.; Milanesi, L.; Pfeffer, U.; Rizzo, R.; Shin, S.-Y.; Xia, J.; Urso, A.
In: BMC Bioinform., Vol. 20, 2019.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - The 2017 Network Tools and Applications in Biology (NETTAB) workshop: Aims, topics and outcomes
T2 - BMC Bioinformatics
AU - Romano, P.
AU - Céol, A.
AU - Dräger, A.
AU - Fiannaca, A.
AU - Giugno, R.
AU - La Rosa, M.
AU - Milanesi, L.
AU - Pfeffer, U.
AU - Rizzo, R.
AU - Shin, S.-Y.
AU - Xia, J.
AU - Urso, A.
N1 - Export Date: 2 March 2020 CODEN: BBMIC Correspondence Address: Romano, P.; IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi 10, Italy; email: paolo.romano@hsanmartino.it Funding details: National Research Council Funding details: National Council for Scientific Research Funding text 1: The last guest lecture was given by Luana Licata, ELIXIR-IIB, Italy. The lecture, titled “ELIXIR-IIB: the Italian Infrastructure for Bioinformatics: a growing support to national and international research in life sciences”, gave an overview on the ELIXIR Italian node and infrastructure for bioinformatics. The node is coordinated by the National Research Council and currently includes 17 centers of excellence among which are research institutes, universities and technological institutions. The infrastructure supports the exchange and development of skills, and the integration of publicly available and internationally recognised Italian bioinformatics resources within the European infrastructure. Funding text 2: The second tutorial was offered by the CNR InterOmics Flagship project. The tutorial, titled “Biological network-based analysis of omics for precision medicine: overview, interaction databases and network diffusion approaches”, was given by Ettore Mosca, Institute of Biomedical Technologies, National Research Council of Italy, Milan, Italy. The tutorial illustrated how the known molecular interactions can be useful in the interpretation of “omics” data for precision medicine, with a main focus on data referable to genes. The first part introduced broad objectives and principles of biological network-based analyses of “omics” data. Then, an overview of the state-of-the art of current datasets from which networks can be defined was given, also in term of their completeness in relation to the coverage of high-throughput technologies and the issues in mapping “omics” data to biological networks. The second part focused on network diffusion-based approaches and illustrated how the principles behind this class of methods have been recently applied to several problems, including patient stratification and gene module extraction. Throughout the tutorial, benefits, limitations and open issues in the field of network-based analysis were underlined, including also software availability and computational cost. References: NETTAB Workshops, , http://www.nettab.org/, Accessed 26 Feb 2019; NETTAB 2017 Workshop, , http://www.igst.it/nettab/2017/, Accessed 26 Feb 2019; Barabási, A.L., Oltvai, Z.N., Network biology: Understanding the cell's functional organization (2004) Nat Rev Genet, 5, p. 101. , https://doi.org/10.1038/nrg1272; Mast, F.D., Ratushny, A.V., Aitchison, J.D., Systems cell biology (2014) J Cell Biol, 206 (6), pp. 695-706. , https://doi.org/10.1083/jcb.201405027; Sompairac, N., Modamio, J., Rmt, F., Barillot, E., Zinovyev, A., Kuperstein, I., Metabolic and signalling network map integration: Application to cross-talk studies and omics data analysis in cancer BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2682-z; Kuperstein, I., Bonnet, E., Nguyen, H.A., Cohen, D., Viara, E., Grieco, L., Atlas of Cancer Signalling Network: A systems biology resource for integrative analysis of cancer data with Google Maps (2015) Oncogenesis, 4 (7), p. e160. , https://doi.org/10.1038/oncsis.2015.19; Noronha A, D., ReconMap: An interactive visualization of human metabolism (2017) Bioinformatics, 33 (4), pp. 605-607. , https://doi.org/10.1093/bioinformatics/btw667; Burgoon, L.D., The need for standards, not guidelines, in biological data reporting and sharing (2006) Nat Biotechnol, 24, p. 1369. , https://doi.org/10.1038/nbt1106-1369; Saito, R., Smoot, M.E., Ono, K., Ruscheinski, J., Wang, P.L., Lotia, S., A travel guide to Cytoscape plugins (2012) Nat Methods, 9, p. 1069. , https://doi.org/10.1038/nmeth.2212; Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J., Appleton, G., Axton, M., Baak, A., The FAIR Guiding Principles for scientific data management and stewardship (2016) Sci Data, 3, p. 160018. , https://doi.org/10.1038/sdata.2016.18; Kuperstein, I., Cohen, D.P., Pook, S., Viara, E., Calzone, L., Barillot, E., NaviCell: A web-based environment for navigation, curation and maintenance of large molecular interaction maps (2013) BMC Syst Biol, 7 (1), p. 100. , https://doi.org/10.1186/1752-0509-7-100; Kuperstein, I., Cohen, D.P., Pook, S., Viara, E., Calzone, L., Barillot, E., NaviCell: A web-based environment for navigation, curation and maintenance of large molecular interaction maps (2013) BMC Syst Biol, 7 (1), p. 100. , https://doi.org/10.1186/1752-0509-7-100; Zhou, Q., Su, X., Wang, A., Xu, J., Ning, K., QC-Chain: Fast and holistic quality control method for next-generation sequencing data (2013) PloS ONE, 8 (4), p. e60234. , https://doi.org/10.1371/journal.pone.0060234; Sangiovannni, M., Granata, I., Shing Thind, A., Guarracino, M., From trash to treasure: Detecting unexpected contamination in unmapped NGS data BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2684-x; Kostic, A.D., Gevers, D., Pedamallu, C.S., Michaud, M., Duke, F., Earl, A.M., Genomic analysis identifies association of Fusobacterium with colorectal carcinoma (2012) Genome Res, 22 (2), pp. 292-298. , http://www.genome.org/cgi/doi/10.1101/gr.126573.111; Lin, Z., Puetter, A., Coco, J., Xu, G., Strong, M.J., Wang, X., Detection of Murine Leukemia Virus in the Epstein-Barr virus-positive human B-cell line JY using a computational RNA-seq based exogenous agent detection pipeline, PARSES (2012) J Virol, pp. JVI-06717. , https://jvi.asm.org/content/86/6/2970; Strong, M.J., O'Grady, T., Lin, Z., Xu, G., Baddoo, M., Parsons, C., Epstein-Barr virus and human herpesvirus 6 detection in a non-Hodgkin's diffuse large B-cell lymphoma cohort by using RNA sequencing (2013) J Virol, 87 (23), pp. 13059-13062. , https://jvi.asm.org/content/87/23/13059; Amadou, A., Hainaut, P., Romieu, I., Role of Obesity in the Risk of Breast Cancer: Lessons from Anthropometry (2013) J Oncol, 2013, p. 19. , http://doi.org/10.1155/2013/906495; Goodwin, P.J., Obesity and Breast Cancer Outcomes: How Much Evidence Is Needed to Change Practice? (2016) J Clin Oncol, 34 (7), pp. 646-648. , https://doi.org/10.1200/JCO.2015.64.7503, PMID: 26712225; De Pergola, G., Silvestris, F., Obesity as a Major Risk Factor for Cancer (2013) J Obes, 11. , http://dx.doi.org/10.1155/2013/291546; Chan, D.S.M., Norat, T., Obesity and Breast Cancer: Not only a Risk Factor of the Disease Curr Treat Options Oncol, 16 (5), p. 22. , https://doi.org/10.1007/s11864-015-0341-9; Granata, I., Troiano, E., Sangiovannni, M., Guarracino, M., Integration of transcriptomic data in a genome-scale metabolic model to investigate the link between obesity and breast cancer BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2685-9; Mardinoglu, A., Agren, R., Kampf, C., Asplund, A., Nookaew, I., Jacobson, P., Integration of clinical data with a genome-scale metabolic model of the human adipocyte (2013) Mol Syst Biol, 9 (1). , http://msb.embopress.org/content/9/1/649; Lee, D., Smallbone, K., Dunn, W.B., Murabito, E., Winder, C.L., Kell, D.B., Improving metabolic flux predictions using absolute gene expression data (2012) BMC Syst Biol, 6 (1), p. 73. , https://doi.org/10.1186/1752-0509-6-73; Creation and Analysis of Biochemical Constraint-based Models: The COBRA Toolbox v3.0, , https://arxiv.org/abs/1710.04038v2, Accessed 26 Feb 2019; Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Cytoscape: A software environment for integrated models of biomolecular interaction networks (2003) Genome Res, 13 (11), pp. 2498-2504. , http://www.genome.org/cgi/doi/10.1101/gr.1239303; Goenawan, I.H., Bryan, K., Lynn, D.J., DyNet: Visualization and analysis of dynamic molecular interaction networks (2016) Bioinformatics, 32 (17), pp. 2713-2715. , http://dx.doi.org/10.1093/bioinformatics/btw187; Khakzad A, M., Greedy de novo motif discovery to construct motif repositories for bacterial proteomes BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2686-8; The MEME Suite, , http://meme-suite.org/, Accessed 26 Feb 2019; Kel, A., Boyarskikh, U., Stegmaier, P., Evshin, I., Mandrik, N., Koschmann, J., Walking pathways with positive feedback loops reveal DNA methylation biomarkers of colorectal cancer BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2687-7; Kel, A.E., (2017) Search for Master Regulators in Walking Cancer Pathways BT - Biological Networks and Pathway Analysis, pp. 161-191. , https://doi.org/10.1007/978-1-4939-7027-8_8, New York: Springer New York; Ongen, H., Andersen, C.L., Bramsen, J.B., Oster, B., Rasmussen, M.H., Ferreira, P.G., Putative cis-regulatory drivers in colorectal cancer (2014) Nature, pp. 512-587. , https://doi.org/10.1038/nature13602; Tomasetti, C., Vogelstein, B., Variation in cancer risk among tissues can be explained by the number of stem cell divisions (2015) Science, 347 (6217), pp. 78-81. , http://science.sciencemag.org/content/347/6217/78; Dumitrescu, R.G., Cotarla, I., Understanding breast cancer risk - Where do we stand in 2005? (2005) J Cell Mol Med, 9 (1), pp. 208-221. , https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1582-4934.2005.tb00350.x; Østerlind A, T., The Danish case-control study of cutaneous malignant melanoma. II. Importance of UV-light exposure (1988) Int J Cancer, 42 (3), pp. 319-324. , https://onlinelibrary.wiley.com/doi/abs/10.1002/ijc.2910420303; Alexandrov, L.B., Nik-Zainal, S., Wedge, D.C., Campbell, P.J., Stratton, M.R., Deciphering Signatures of Mutational Processes Operative in Human Cancer (2013) Cell Rep, 3 (1), pp. 246-259. , https://doi.org/10.1016/j.celrep.2012.12.008; Shiraishi, Y., Tremmel, G., Miyano, S., Stephens, M., A Simple Model-Based Approach to Inferring and Visualizing Cancer Mutation Signatures (2015) PLoS Genet, 11 (12), pp. 1-21. , https://doi.org/10.1371/journal.pgen.1005657; Krüger, S., Piro, R., DecompTumor2Sig: Identification of mutational signatures active in individual tumors BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2688-6; Quadrini, M., Tesei, L., Merelli, E., An algebraic language for RNA pseudoknots comparison BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2689-5; Gilbert, D., Heiner, M., Ghanbar, L., Chodak, J., Spatial quorum sensing modelling using coloured hybrid Petri nets and simulative model checking BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2690-z; Lancia, G., Bafna, V., Istrail, S., Lippert, R., Schwartz, R., (2001) SNPs Problems, Complexity, and Algorithms BT - Algorithms - ESA 2001, pp. 182-193. , https://link.springer.com/chapter/10.1007/3-540-44676-1_15, Berlin: Springer Berlin Heidelberg; Rhee, J.K., Li, H., Joung, J.G., Hwang, K.B., Zhang, B.T., Shin, S.Y., Survey of computational haplotype determination methods for single individual (2016) Genes Genom, 38 (1), pp. 1-12. , https://doi.org/10.1007/s13258-015-0342-x; Tangherloni, A., Spolaor, S., Rundo, L., Nobile, M., Cazzaniga, P., Mauri, G., GenHap: A Novel Computational Method Based on Genetic Algorithms for Haplotype Assembly BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2691-y; Zandonà A, V., A Dynamic Bayesian Network model for the simulation of Amyotrophic Lateral Sclerosis progression BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2692-x; Atassi, N., Berry, J., Shui, A., Zach, N., Sherman, A., Sinani, E., The PRO-ACT database (2014) Neurology, 83 (19), pp. 1719-1725. , http://n.neurology.org/content/83/19/1719; Vogenberg, F.R., Isaacson Barash, C., Pursel, M., Personalized medicine: Part 1: Evolution and development into theranostics (2010) P T Peer-Reviewed J Formul Manag, 35 (10), pp. 560-576. , https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2957753/; Daly, A.K., Pharmacogenetics: A general review on progress to date (2017) Br Med Bull, 124 (1), pp. 65-79. , http://dx.doi.org/10.1093/bmb/ldx035; Thorn, C.F., Klein, T.E., Altman, R.B., PharmGKB: The Pharmacogenomics Knowledge Base BT - Pharmacogenomics: Methods and Protocols (2013) Totowa: Humana Press, pp. 311-320. , https://doi.org/10.1007/978-1-62703-435-7_20; Monnin, P., Legrand, J., Husson, G., Ringot, P., Tchechmedjiev, A., Jonquet, C., PGxO and PGxLOD: A reconciliation of pharmacogenomic knowledge of various provenances, enabling further comparison BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2693-9; Ferraro Petrillo, U., Sorella, M., Cattaneo, G., Giancarlo, R., Rombo, S.E., Analyzing big datasets of genomic sequences: Fast and scalable collection of k-mer statistics BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2694-8; Navas-Delgado, G., I, VIGLA-M: Visual gene expression data analytics BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2695-7; Fassetti, F., Giallombardo, C., Leone, O., Palopoli, L., Rombo, S.E., Saiardi, A., FEDRO: A software tool for the automatic discovery of candidate ORFs in plants with c →u RNA editing BMC Bioinformatics, , https://doi.org/10.1186/s12859-019-2696-6; Fassetti, F., Giallombardo, C., Leone, O., Palopoli, L., Rombo, S.E., Saiardi, A., Discovering New Proteins in Plant Mitochondria by RNA Editing Simulation (2016) Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies, 3, pp. 182-189. , https://www.scitepress.org/papers/2016/56649/56649.pdf, BIOINFORMATICS, (BIOSTEC 2016). INSTICC. SciTePress
PY - 2019
Y1 - 2019
N2 - The 17th International NETTAB workshop was held in Palermo, Italy, on October 16-18, 2017. The special topic for the meeting was "Methods, tools and platforms for Personalised Medicine in the Big Data Era", but the traditional topics of the meeting series were also included in the event. About 40 scientific contributions were presented, including four keynote lectures, five guest lectures, and many oral communications and posters. Also, three tutorials were organised before and after the workshop. Full papers from some of the best works presented in Palermo were submitted for this Supplement of BMC Bioinformatics. Here, we provide an overview of meeting aims and scope. We also shortly introduce selected papers that have been accepted for publication in this Supplement, for a complete presentation of the outcomes of the meeting. © 2019 The Author(s).
AB - The 17th International NETTAB workshop was held in Palermo, Italy, on October 16-18, 2017. The special topic for the meeting was "Methods, tools and platforms for Personalised Medicine in the Big Data Era", but the traditional topics of the meeting series were also included in the event. About 40 scientific contributions were presented, including four keynote lectures, five guest lectures, and many oral communications and posters. Also, three tutorials were organised before and after the workshop. Full papers from some of the best works presented in Palermo were submitted for this Supplement of BMC Bioinformatics. Here, we provide an overview of meeting aims and scope. We also shortly introduce selected papers that have been accepted for publication in this Supplement, for a complete presentation of the outcomes of the meeting. © 2019 The Author(s).
KW - Network tools
KW - Oral communication
KW - Personalised medicines
KW - Scientific contributions
KW - bioinformatics
KW - biology
KW - publication
KW - review
KW - genetics
KW - genomics
KW - health care delivery
KW - human
KW - Italy
KW - neoplasm
KW - personalized medicine
KW - procedures
KW - Computational Biology
KW - Delivery of Health Care
KW - Genomics
KW - Humans
KW - Neoplasms
KW - Precision Medicine
U2 - 10.1186/s12859-019-2681-0
DO - 10.1186/s12859-019-2681-0
M3 - Article
VL - 20
JO - BMC Bioinform.
JF - BMC Bioinform.
SN - 1471-2105
ER -