SMB Digest January 4, 2017

ISSN 1086-6566


Information about the Society for Mathematical Biology, including an application for membership, may be found in the SMB Home Page,

Access the Bulletin of Mathematical Biology, the official journal of SMB, at

Inquiries about membership or BMB fulfillment should be sent to membership(at)smb(dot)org 

    Issue's Topics:
      Education Query from a high school teacher
      MBI National Mathematical Biology Colloquium, Wednesday January 11
      CfP: Artificial Immune Systems: Algorithms, Simulation, Modelling ...
      Short Course: Matrix Approaches to Health Demography, 13-24 March
      2017 AAi Short Courses
      Your New Springer Books in January
      WIREs Syst Biol Med Content Alert (New Articles)
      Postdoc: Mathematical and Computational Modelling ..., Notre Dame, USA
      Updated NSF funding opportunity, BIGDATA: Critical Techniques, ...
      Selected NIH Intramural Research and other job openings - Jan. 2017
      SMBnet Reminders

From: Richard Kurtz <>
Date: Fri, Dec 30, 2016 at 1:01 PM
Subject: Education Query from a high school teacher

I am writing on behalf of 3 of my students at my high School, Commack High
School, NY. They are working on a computational biology project and we
were hoping to find a scientist out there who may be interested in giving
us some help/advise. Below is the letter my students composed.

We would be appreciative for any help to answer our questions and concerns. We
have a fair understanding of computer programming, most specifically with
Python. However, we are novices to the art of bioinformatics and computational
biology. Our goal is to analyze the differences that influence the expression
of Tay-Sachs between the late onset and early onset varieties. With this core
idea in mind, what procedures do you imagine we could carry out to address
this topic? What preexisting programs are there that we can implement in our
research? Have you done or do you know of any projects or procedures that
have been previously done in other fields that we can model our work after?

Thank you again for offering your assistance,


From: Tony Nance <>
Date: Tue, Jan 3, 2017 at 12:31 PM
Subject: MBI National Mathematical Biology Colloquium, Wednesday January 11

MBI National Mathematical Biology Colloquium
Wednesday January 11, 2017 at Noon Eastern Time

Leah Edelstein-Keshet (Mathematics, British Columbia)

Navigating Biochemical Pathways for Cell Polarization and Motility (A Personal
Many cell types, including cells of the immune system, are able to polarize
and crawl in response to chemical or mechanical stimuli. In this way, they
can perform vital functions such as immune surveillance, wound healing,
and tissue development. I will describe our efforts to understand the
underlying biochemistry governing the initial direction sensing, polarization,
cell shape change, and motility. While much of the biology is undergoing
rapid discovery, we have found that mathematical ideas supply additional
tools. Such tools help to decipher underlying mechanism, to weed between
competing hypotheses, and to suggest new experimental tests. On the same
journey, we also encountered some new and interesting mathematics.

This online series gives individuals and groups the opportunity to watch talks
and to interact with distinguished speakers. Details of how to connect to the
talks are available on the MBI website at

Upcoming talks:

Feb 15  JOEL COHEN (Laboratory of Populations, Rockefeller U)
The Variation is the Theme: Taylor's Law from Chagas Disease Vector Control
to Tornado Outbreaks

Mar 15  URI ALON (Molecular Cell Biology, Weizmann Institute)
Design Principles in Biology

Apr 12  JAMES KEENER (Mathematics, Utah)
Cell Physiology: Making Diffusion Your Friend


From: Mario Pavone <>
Date: Sat, Dec 31, 2016 at 7:03 AM
Subject: CfP: Artificial Immune Systems: Algorithms, Simulation, Modelling ...


Artificial Immune Systems: Algorithms, Simulation, Modelling & Theory
IEEE CEC 2017 Special Session
June 20-23, 2017, Donostia - San Sebastián, Spain

*** SUBMISSION deadline: January 16, 2017


From: Hal Caswell <>
Date: Sun, Jan 1, 2017 at 3:47 PM
Subject: Short Course: Matrix Approaches to Health Demography, 13-24 March

IDEM 134
Matrix Approaches to Health Demography
Max Planck Institute for Demographic Research
13-24 March 2017

Hal Caswell

This course will introduce matrix methods for health demography, including
measures of healthy longevity, disease progression, population projection,
and cause-of-death analysis. We will introduce matrix methods that extend
the usual analyses in two directions, by incorporating variance and
stochasticity into the analyses, and including sensitivity analyses to
quantify the effects of parameters on the results.

The class will introduce methods based on Markov chains, Markov chains with
rewards, multistate matrix models, and matrix calculus. These methods will
be compared to traditional approaches, and applied to data on prevalence
of health conditions, incidence of disease and disability, population
projections, and causes of death.

Although the applications will focus on human populations, all of these
topics have direct (or, at least potential) applications in animal and
plant demography. Biodemographers and population biologists interested in
new perspectives in demographic analysis are encouraged to apply (deadline
29 January 2017).

For details and application information, see:


From: Colin Wise <>
Date: Tue, Jan 3, 2017 at 7:29 PM
Subject: 2017 AAi Short Courses

Dear Colleague,

2017 AAi Short Courses

Happy New Year for 2017.

Thank you for your support in 2016 and we look forward to seeing you and your
colleagues in 2017.


From: Springer <>
Date: Mon, Jan 2, 2017 at 1:46 AM
Subject: Your New Springer Books in January


>> Mathematical and Computational Biology <<

Systems Pharmacology and Pharmacodynamics
Book Series: AAPS Advances in the Pharmaceutical Sciences Series, Vol. 23
Editor/s: Mager, Donald E.; Kimko, Holly H.C.

Variational Methods in Molecular Modeling
Book Series: Molecular Modeling and Simulation
Editor/s: Wu, Jianzhong


From: <>
Date: Sun, Jan 1, 2017 at 2:54 PM
Subject: WIREs Syst Biol Med Content Alert (New Articles)

Wiley Interdisciplinary Reviews: Systems Biology and Medicine
© Wiley Periodicals, Inc.


Computational models of the neural control of breathing
Yaroslav I. Molkov, Jonathan E. Rubin, Ilya A. Rybak and Jeffrey C. Smith


Toward modeling locomotion using electromyography-informed 3D models:
application to cerebral palsy
M. Sartori, J. W. Fernandez, L. Modenese, C. P. Carty, L. A. Barber, K.
Oberhofer, J. Zhang, G. G. Handsfield, N. S. Stott, T. F. Besier, D. Farina
and D. G. Lloyd

Quantitative approaches for investigating the spatial context of
gene expression
Je H. Lee


You have free access to this content

Cancer and inflammation
Lance L. Munn


From: Brajendra Kumar Singh <>
Date: Wed, Dec 28, 2016 at 7:46 PM
Subject: Postdoc: Mathematical and Computational Modelling ..., Notre Dame, USA

POST-DOCTORAL FELLOW POSITION in Mathematical and Computational Modelling
of Neglected Tropical Diseases

A Postdoctoral Research Fellow position is available immediately in the
inter-disciplinary Global Epidemiology and Biostatistics Group led by Prof.
Edwin Michael at the University of Notre Dame in the Department of Biological
Sciences and the Eck Institute for Global Health, to develop new mathematical,
data assimilation, and computational frameworks for modeling neglected
vector-borne parasitic infections, focusing on  diseases ranging from
lymphatic filariasis, onchocerciaisis to dengue.

Detailed information is available at


From: Henry Warchall <>
Date: Tue, Jan 3, 2017 at 1:05 PM
Subject: Updated NSF funding opportunity, BIGDATA: Critical Techniques, ...

Dear Colleagues,

An updated NSF program solicitation (NSF 17-534) is now available:

 Critical Techniques, Technologies, and Methodologies for
 Advancing Foundations and Applications of
 Big Data Sciences and Engineering (BIGDATA)

Please see

for details.

Full Proposal Window:  March 15, 2017 - March 22, 2017


From: "Owens, Roland (NIH/OD) [E]" <>
Date: Tue, 3 Jan 2017 19:27:12 +0000
Resent-from: Raymond Mejía <>
Subject: Selected NIH Intramural Research and other job openings - Jan. 2017

Chief and Senior Investigator
Biostatistics and Bioinformatics Branch, NICHD
(Review of applications begins: January 13)

The Division of Intramural Population Health Research is located within
the Eunice Kennedy Shriver National Institute of Child Health and Human
Development and invites qualified candidates to apply for the position
of Chief and Senior Investigator of the Biostatistics and Bioinformatics
Branch. As one of three intramural branches in the Division, the Biostatistics
and Bioinformatics Branch mission is to develop novel statistical methods
motivated by the Division's population health research that includes
human fecundity and fertility, pregnancy, and child and adolescent
health and behavior. In addition, Branch scientists serve as statistical
co-investigators on all etiologic and interventional research in keeping
with the team science research paradigm practiced by the Division. The
Branch's mission also includes a strong commitment to mentoring trainees
at varying career stages and professional service.

As an intramural entity, the Branch is expected to develop innovative
methodologic and collaborative research that uses the rich trans-disciplinary
environment of the Division and the NIH Intramural Research Program. This
expectation includes developing and implementing methods that support
original research seeking to answer critical data gaps, and in the
analysis of a vast array of databases from completed and ongoing research
studies. The Biostatistics and Bioinformatics branch currently houses 4
investigators, with room for growth. A description of the Branch may be
found at,
and an overview of all Division research is summarized in the Division's

The Branch Chief must be a dynamic leader who provides scientific,
administrative and fiscal leadership, while maintaining his/her own
original methodologic and collaborative research. Candidates must have an
earned doctoral degree in biostatistics, statistics or a closely related
quantitative field. The successful candidate must be an internationally
recognized methodologist whose accomplishments are commensurate with the
academic rank of a tenured full professor, as demonstrated by a strong
upward trajectory of high quality statistical publications, a trajectory
of high quality and impact collaborative publications, an international
reputation, extramural funding (for academic candidates), and a clear vision
of biostatistics' and bioinformatics' essential role in population health
research. The Chief is expected to lead in strengthening current research
areas and in developing new areas of expertise to address increasingly
challenging designs and analyses, including priorities such as bioinformatics
and causal inference. The Chief is expected to lead in developing and
implementing the infrastructure and culture of reproducible research.s 
The position requires excellent inter-personnel and communication skills,
and experience leading trans-disciplinary scientific teams and recruiting
early stage biostatisticians are highly desirable. The Chief will serve as
a member of the Division's senior leadership working to further the Division
and Institute's vision and mission.

The Branch Chief will be eligible for tenure, at a salary commensurate with
his/her credentials and experience. Full federal government benefits will
be provided, including leave, health and life insurance, long-term care
insurance, retirement plan, and savings plan (401k equivalent). Interested
candidates should submit the following items: Curriculum vitae; brief (2-3
pages) cover letter that summarizes professional training and experience
in the following areas: leadership, management, administration, research,
professional service, and mentoring; brief (2-3 pages) vision statement for
the Branch; and names, affiliations, and contact details for three references
(who will only be contacted following an interview).

Please email these materials as one package to: Ms. Adrienne Lonaberger;
Program Analyst, DIPHR, NICHD; 6710B Rockledge Drive; Room 3141D;
Bethesda, MD 20892; 301-496-6324; or All inquiries
about the position should be directed to the Committee Chair: Dr. Enrique
Schisterman; Chief and Senior Investigator; Epidemiology Branch, DIPHR,
NICHD; 6710B Rockledge Drive, Room 3136; Bethesda, MD 20892; 301-435-6893, Complete applications received by January 13, 2017,
will be considered for a first round of interviews, but applications will be
accepted until the position is filled. The selected candidate is expected
to assume the position and be onsite by July 1, 2017. HHS, NIH, and NICHD
are equal opportunity employers.

Chief Data Scientist
Division of Cancer Epidemiology and Genetics, NCI
(Review of applications begins: January 13)

The Division of Cancer Epidemiology and Genetics (DCEG) of the National
Cancer Institute is recruiting an accomplished, senior investigator to
serve as Chief Data Scientist in the Office of the Director, DCEG. The
mission of DCEG is to discover environmental and genetic determinants
of cancer, and to identify new approaches to cancer prevention through
epidemiological research. The Chief Data Scientist will lead efforts to
define new infrastructure to extract, manage, and analyze data in a scalable
way to support epidemiological research within the Division. He/she will
also be provided with the resources to lead an internationally-recognized
scientific research program in big data analytics for cancer research.

The incumbent will play a leadership role and work closely with DCEG
investigators to conceptualize, design, and develop analytic solutions
for high dimensional, complex data, including the ability to articulate
data-intensive analytics using cloud computing infrastructure and
user-facing web computing/mobile development. Responsibilities include
creating a roadmap for implementing data and analytics strategy, including
infrastructure design and development of data models; leading efforts to
develop scalable, innovative approaches to extract, manage, and analyze
data; and providing oversight and procedures for modeler/statistical team
members on key projects in collaboration with the Biostatistics Branch. The
incumbent will also develop a vision for data analytics architecture and
workflows for epidemiologic studies; establish data policies, standards,
organization and enforcement of data governance; develop innovative
approaches to link internal systems with external data; lead collaborations
within other agencies of the federal government, academic institutions,
and healthcare industry to invent, pilot, and operationalize emerging data
science solutions, methods, and processes; and drive data science innovation
in epidemiology through active participation in professional societies,
key events, and public-private partnerships. He/she will work closely with
the NCI Center for Biomedical Informatics and Information Technology to
coordinate DCEG solutions with NCI-wide programs, and will coordinate the
DCEG data strategy with other NIH Institutes and Programs.

The successful candidate must hold a Ph.D. or equivalent doctoral degree
in computer science, mathematics, statistics or a related science and have
strong written and verbal communication skills. He/she must have a minimum
of five years of relevant experience in data science, and demonstrate
experience with algorithms for complex data integration and capture as
well as application of advanced data analytics, including data mining and
visualization. The incumbent must demonstrate deep understanding of database
design and structure. Experience should include work with applications
backed by data-intensive infrastructure and statistical applications. The
incumbent must demonstrate the ability to conduct high-quality, original
research that has been published in peer-reviewed scientific journals
and presented at scientific meetings. He\she must also have experience
in developing and mentoring staff at all levels and building an internal
capacity to deliver high quality and highly innovative analytics services.  

The Chief Data Scientist will be eligible for a tenured appointment at
a salary commensurate with his/her qualifications and experience.  Full
Federal benefits including leave, health and life insurance, long-term
care insurance, retirement, and savings plan (401k equivalent) will be
provided. Interested individuals should send a cover letter summarizing
research interests, accomplishments, and scientific administrative experience;
curriculum vitae and bibliography; a list of up to five key publications;
and the names and addresses of three references to: Ms. Catherine
McClave, Division of Cancer Epidemiology and Genetics, National Cancer
Institute,  Applications received by
January 13, 2017 will be considered for a first round of interviews, but
applications will be accepted until the position is filled.  The DHHS and
NIH are equal opportunity employers.

Tenure-Track/Tenure-Eligible Investigator
Biostatistics Branch, NCI-DCEG
(deadline: February 28)

The Biostatistics Branch (BB) in the Division of Cancer Epidemiology and
Genetics (DCEG), National Cancer Institute (NCI), National Institutes of
Health (NIH), Department of Health and Human Services (DHHS), is recruiting
for a tenure-track/tenure eligible position. BB statisticians develop
statistical research programs and actively collaborate both in cutting-edge
studies of genetic, lifestyle, and other environmental causes of cancer,
as well as in studies of cancer prevention, descriptive and clinical
epidemiology.  Statistical research is typically motivated by challenges
encountered in DCEG studies, such as choosing an efficient study and
sampling design, optimally combining data from multiple sources such as
electronic medical records, genetic data bases, disease and bio-specimen
registries, as well as designing validation studies and methods to evaluate
and correct for measurement error in exposures and disease outcomes. The
branch has active methodological research programs in areas that include 1)
absolute risk prediction, 2) analysis of longitudinal and survival data,
3) analysis and temporal and spatially related incidence data, and 4) the
analysis of "omics" data that includes the analysis of data from cutting-edge
next generation sequencing.

We anticipate increasing opportunities for methodological and applications
research in the analysis of complex biomarker and exposure related data,
longitudinal and correlated data, as well as in high-dimensional data analysis
including "omics" data integration. However, because of the breadth of the
problems we face, we seek qualified applicants with all areas of statistical
expertise in methods, including but not restricted to semiparametric
and survival analysis, functional data analyses, missing data and causal
inference, Bayesian and non-Bayesian computations, and network theory.

Applications will be evaluated on demonstrated potential to develop a
creative, independent program of statistical research applicable to cancer
epidemiology and genetics, and to collaborate effectively on epidemiologic
studies. Applicants should have a doctorate in biostatistics, statistics
or a related field, knowledge of the basic approaches used in cancer
epidemiology, and knowledge of biostatistical theory and methods. A record
of publications demonstrating an ability to conduct independent research
on statistical methods is required. Publications documenting collaborative
research in epidemiologic, clinical, biomedical, or biological sciences are
highly desirable. The successful candidate should have strong communication
skills to discuss scientific issues with non-statistical colleagues and to
write scientific papers.

Salary is commensurate with research experience and accomplishments. The
incumbent will receive research support from the intramural research
program of NIH for computer programming and recruiting a post-doctoral
fellow. Interested individuals should send a cover letter; curriculum vitae
and bibliography; a brief summary of research experience, accomplishments and
research interests and goals; copies of three publications or preprints;
and three letters of reference to: Ms. Linda Littlejohn; Division
of Cancer Epidemiology and Genetics; National Cancer Institute; 9609
Medical Center Drive, Suite 7E328, MSC 9775; Bethesda, MD 20892-9775. 
Or e-mail: The closing date for applications is
February 28, 2017. Please contact Dr. Paul Albert (phone 240-276-7593
or for questions about the position. DHHS, NIH,
and NCI are equal opportunity employers.

The NIH Intramural Research Program

Link to Fellowships and Positions of Interest to fellows


Subject: SMBnet Reminders To subscribe to the SMB Digest please point your browser at and complete the subscription information. Alternatively, if you prefer to simply receive notice when the next issue is available, send mail to with "subscribe SMBnet Your Name" in the body of the mail (omit the quotes and include your name). After you subscribe, you will receive a greeting with additional information. Submissions to appear in the SMB Digest should be sent to SMBnet(at)smb(dot)org. Items of interest to the mathematical biology community may be submitted for inclusion in the SMBnet archive. See instructions at . The SMB Digest is also available on the SMB Home Page at The contents of this publication may be reproduced in whole or in part with attribution.