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Subject: Society for Mathematical Biology Digest
SMB Digest May 11, 2016 Volume 16 Issue 19
ISSN 1086-6566
Editor: Alex Fletcher digest.alex(at)gmail(dot)com
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Issue's Topics:
Combined CHARME-EMBNet & NETTAB 2016 Workshop..., Oct 25-26, Italy
Research Scientist: Computational Bioinformatician, BHSAI, USA
PhD: Energy variability & genetic decision making..., Birmingham, UK
SMBnet Reminders
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Date: Thu, May 5, 2016 at 10:51 AM
Subject: Combined CHARME-EMBNet & NETTAB 2016 Workshop..., Oct 25-26, Italy
Combined CHARME ? EMBnet and NETTAB 2016 Workshop
Reproducibility, standards and SOP in bioinformatics
Oct 25-26, National Research Council, Piazzale Aldo Moro 7, Rome, Italy
Next deadline: Submission of abstracts for oral communications: May 30, 2016
*CALL FOR ABSTRACTS FOR ORAL COMMUNICATIONS AND POSTERS*
The Workshop 'Reproducibility, standards and SOP in bioinformatics' is
co-organised by the COST European Action CHARME (CA15110), EMBnet (The
Global Bioinformatics Network) and NETTAB (International Workshop Series on
Network Tools and Applications for Biology). It is hosted by the ELIXIR-ITA
Node and will be held at the Italian CNR (National Research Council) head
quarter, in Rome.
The workshop will be preceded by a GOBLET/ELIXIR-ITA Tutorial and a ELIXIR
Hacktahon on Monday 24th and followed by the EMBNet Annual General Meeting
on Thursday 27th.
Keynote Speakers (confirmed only):
- Jacques van Helden, Université d'Aix-Marseille (AMU), Marseille, France
- Barend Mons, Leiden University Medical Center (LUMC), Leiden, Netherlands
- Further Keynote speakers will be announced soon.
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Date: Tue, May 10, 2016 at 3:52 PM
Subject: Research Scientist: Computational Bioinformatician, BHSAI, USA
The Henry M. Jackson Foundation for the Advancement of Military Medicine,
Inc. (HJF) is seeking a Computational Bioinformatician to support the U.S.
Army Medical Research and Materiel Command's Biotechnology High Performance
Computing Software Applications Institute (BHSAI) [
www.BHSAI.org]. HJF
provides scientific, technical, and programmatic support services to the
BHSAI. This opening is for dynamic bioinformatics research scientists
interested in working in multiple cross-disciplinary research projects.
Responsibilities:
The Bioinformatics Research Scientist is responsible for advancing
scientific knowledge by developing and applying their knowledge to original
research problems in Military Medicine. The Research Scientist will apply
their experiences in the analysis, collection, mining, and integration of
multiple high-throughput datasets using computational bioinformatics and
systems biology methods to understand chemical and biological interactions
at the cellular and organism level.
Foreign nationals are welcome to apply. U.S. citizenship or permanent
resident status is not required. This position is located in Frederick,
Maryland.
The candidate is expected to simultaneously work on multiple projects,
involving a diverse and interdisciplinary team of scientists across multiple
laboratories.
For further details, see:
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Date: Tue, May 10, 2016 at 2:46 PM
Subject: PhD: Energy variability & genetic decision making..., Birmingham, UK
Title: Energy variability and genetic decision making in stochastic cells
Supervisors: (Dr Iain Johnston) and Prof George Bassel
FindAPhD entry:
Description:
Why do some cancer cells die immediately in response to chemotherapy, while
others remain in a growing tumour? How do stem cells decide which tissue to
form, and when to do so? Understanding cellular decision making is crucial
in our attempts to predict how diseases will progress and to understand how
cell-to-cell differences arise in biology. These decisions are often made by
networks of interacting genes acting as biological "processors", with genes
modulating each others' expression and governing cell behaviour [1]. A vital
feature of these networks, often neglected in their analysis, is that they
are embedded in a world subject to physical constraints: the processes
involved in gene interactions require a source of energy, and take place in
the chaotic and noisy environment that is the biological cell.
Energy and noise are of central importance in cellular decisions: research
from IGJ and others has shown that variability in mitochondria (fundamental
energy sources in the cell) modulates stem cell fate choices, and that
random influences (including collisions between molecules, and partitioning
at cell divisions) have profound effects on cellular decisions [2].
Descriptions of gene regulation often omit these important dependences and
so are only of limited use in predictive biomedical modelling, particularly
in personalised medicine where biological heterogeneity is a key focus. Our
ability to unify and harness biological "big data", particularly large-scale
omics measurements of noisy transcript and protein populations, also suffers
from this lack of a physical framework to quantify uncertainty and
distinguish functional and spurious connections between genes. Clearly,
appropriate physical models for the energy dependence and stochastic
dynamics of gene regulation are required.
This transformative project will develop, in concert, new modelling
approaches to provide a bottom-up physical description of these important
features, and new statistical tools forging a connection between these
models and a wealth of currently available, large-scale, heterogeneous data.
The researcher will use tools from stochastic processes [2, 3], dynamical
systems [2, 4], and statistical inference (including likelihood-free
approaches) [3, 5] to develop a unified descriptive and predictive theory
linking regulation of energy-dependent and stochastic gene expression with
noisy data. Some experience with these fields, and/or with biophysics/systems
biology, will be helpful, but prior experience with biological topics is not
essential. Through this research we aim to understand physical features
governing variability in cellular decision making, to improve the reliability
of in silico predictions of the behaviour of regulatory motifs and biological
pathways (including stem cell fate decisions and cell death triggers), and
to increase the statistical and interpretative power of omics data for
understanding biology and disease.
Funding Notes: Funding available for three years from the EPSRC, for UK or
EU students only.
References:
[1] Karleback & Shamir, Nat Rev Mol Cell Biol 9 770 (2008)
[2] Johnston et al., PLoS Comput Biol 8 e1002416 (2012)
[3] Johnston et al., eLife 4 e07464 (2015)
[4] Wang et al., Biophys J 99 29 (2010)
[5] Johnston, Stat App Genet Mol Biol 13 379 (2014)
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Subject: SMBnet Reminders
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