Biophysical Reviews

, Volume 9, Issue 4, pp 297–298 | Cite as

Modelling, inference and big data in biophysics

Letter to the Editor

Abstract

In recognition of the increasing importance of big data in biophysics, a new session called ‘Modelling, inference, big data’ is incorporated into the IUPAB/EBSA Congress on 18 July 2017 at Edinburgh, UK.

References

  1. Campbell KR, Yau C (2016) Order under uncertainty: robust differential expression analysis using probabilistic models for Pseudotime inference. PLoS Comput Biol 12:e1005212CrossRefPubMedPubMedCentralGoogle Scholar
  2. Kamali AH, Giannoulatou E, Chen TY, Charleston MA, McEwan AL, Ho JWK (2015) How to test bioinformatics software? Biophys Rev 7:343–352CrossRefPubMedPubMedCentralGoogle Scholar
  3. Pierson E, Yau C (2015) ZIFA: dimensionality reduction for zero-inflated single-cell gene expression analysis. Genome Biol 16:241CrossRefPubMedPubMedCentralGoogle Scholar
  4. Troup M, Yang A, Kamali AH, Giannoulatou E, Chen TY, and Ho JWK (2016) A Cloud-based Framework for Applying Metamorphic Testing to a Bioinformatics Pipeline. In Proceedings of the 1st International Workshop on Metamorphic Testing. p 33–36Google Scholar
  5. Yang A, Troup M, Lin P, Ho JWK (2017) Falco: a quick and flexible single-cell RNA-seq processing framework on the cloud. Bioinformatics 33:767–769PubMedGoogle Scholar

Copyright information

© International Union for Pure and Applied Biophysics (IUPAB) and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Victor Chang Cardiac Research InstituteDarlinghurstAustralia
  2. 2.St. Vincent’s Clinical SchoolThe University of New South WalesDarlinghurstAustralia
  3. 3.School of Life SciencesUniversity of BedfordshireLutonUK

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