Dahlquist:BOSC ISMB 2016 Notes

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BOSC/NetBio SIG Day 1 2016-07-08

• Megan Crow spoke at NetBio Sig on Single-cell gene networks from co-expression
  • mentioned review on single cell RNA Seq, Grün, D., & van Oudenaarden, A. (2015). Design and analysis of single-cell sequencing experiments. Cell, 163(4), 799-810.
  • bar code RNAs before PCR amplification
• MultiQC: Aggregate results from bioinformatics analyses across many samples into a single report
• BOSC Keynote: Jennifer Gardy who is an Assistant Professor of Population and Public Health at the University of British Columbia and a Senior Scientist at the British Columbia Centre for Disease Control (BCCDC)
  • Slides: The open-source outbreak: can datga prevent the next pandemic?
• Blog summary of BOSC at GigaScience
• Docker

BOSC SIG Day 2 2016-07-09

• MetaR from Fabien Campagne lab
  • potentially collaborate on a grant; broader impacts of teaching MetaR to undergrads
• GenePattern Notebooks
  • an integrative analytical environment for genomic research; can do RNAseq analysis
  • available on Indiana University supercomputer cluster
• ReportMD
  • uses R markdown to generate linked HTML reports

ISMB Day 1 2016-07-10

• COSI/SIG SysMod (formerly BioPathways)
• iPath: Interactive Pathways Explorer
• Talk by Lars Juhl Jensen
  • STRING-DB, when comparing data from different protein-protein interaction data, need to calibrate raw quality scores against gold standard (KEGG), see von Mering et al 2005
  • text-mining snafu, human gene nomenclature committee approved human gene called "SDS"
• Talk by Natasa Przulj
  • http://www.nature.com/articles/srep04547 [Yaveroğlu, Ö. N., Malod-Dognin, N., Davis, D., Levnajic, Z., Janjic, V., Karapandza, R., ... & Pržulj, N. (2014). Revealing the hidden language of complex networks. Scientific reports, 4.]
    • small motifs/legos in networks
  • Nataša Pržulj, Noël Malod-Dognin (2016) Network analytics in the age of big data Science 08 Jul 2016:Vol. 353, Issue 6295, pp. 123-124 DOI: 10.1126/science.aah3449
• Oxford Journal Biology Methods and Protocols
  • talked to Jennifer Boyd at the booth and suggested the ability to update published protocols with new versions.
• Books
  • Gandrud, C. (2013). Chapman & Hall/CRC The R Series : Reproducible Research with R and R Studio. Bosa Roca, US: CRC Press. Retrieved from http://electra.lmu.edu:2110
    • library has e-book, but it looks like it is the first edition instead of second edition, limited to a certain number of pages
  • Korpelainen, E., Tuimala, J., & Somervuo, P. (2014). Chapman & Hall/CRC Mathematical and Computational Biology : RNA-seq Data Analysis : A Practical Approach. Boca Raton, US: Chapman and Hall/CRC.
    • library has e-book, limited to a certain number of pages.

ISMB Day 2 2016-07-11

Workshop on Education in Bioinformatics (WEB)

• Phil Bourne: The NIH Commons: A Cloud-based Training Environment
  • Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., ... & Bouwman, J. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific data, 3.
  • NIH Data Commons
  • Instead of funding individual investigators for computational infrastructure, give them credit to use NIH cloud instead, would include training.
• Nirav Merchant: How to Scale Science and People Using the Cloud (slides available after conference on ISMB app)
  • University of Arizona
  • "computational thinking had become central to our course work"
  • local, in-house computational expert: "victim of their own success (denial of service attacks on their availability)"
  • users want (chair), send them to home depot
    • Happy Birthday Ikea, here's your cake.x
  • Democratizing Innovation, Eric Von Hippel
  • need managed cloud: CyVerse Atmosphere, iPlant Collaborative, Jetstream
• Matthew Vaughn: Packaging computational biology tools for broad distribution and ease-of-reuse (need to get slides)
• Panel includes these three plus Annette McGrath of the Australian Bioinformatics Network

Talks

• David Gibbs: Solving the influence maximization problem on biological networks; a case study involving the cell cycle regulatory network in Saccharomyces cerevisiae
  • software on GitHub
• Scott Simpkins: Scalable tools for quantitative analysis from sequencing-based chemical-genetic genetic interaction screens
  • BEAN-counter

Posters

• O30 - Explicit Modeling of Differential RNA Stability Improves Inference of Transcription Regulation Networks by Konstantine Tchourine , NYU - Center for Genomics and Systems Biology
  • when using YEASTRACT data, require 1 direct and 2 direct evidence
  • Kemmeran KO dataset
  • Sameith, K., Amini, S., Koerkamp, M. J. G., van Leenen, D., Brok, M., Brabers, N., ... & Apweiler, E. (2015). A high-resolution gene expression atlas of epistasis between gene-specific transcription factors exposes potential mechanisms for genetic interactions. BMC biology, 13(1), 1.

Other notes

• Goblet: Global Organisation for Bioinformatics Learning, Education & Training
• Android 6 marshmallow allows you to deny access to apps (like location, etc.)
• CatterPlots!!!!!
• Conesa, A., Madrigal, P., Tarazona, S., Gomez-Cabrero, D., Cervera, A., McPherson, A., ... & Mortazavi, A. (2016). A survey of best practices for RNA-seq data analysis. Genome biology, 17(1), 1.