2021 Autumn Newsletter

Ruth Bowness (University of Bath), Reginald L. McGee II (College of the Holy Cross), Fiona Macfarlane (University of St Andrews), Jacob Scott (Lerner Research Institute, Cleveland Clinic), and Alys Clark (University of Auckland).
  1. News – updates from: 
    • SMB subgroups
    • Bulletin news
    • Mathematical podcast
    • Upcoming conferences
  2. People – Interviews with Michael Savageau, University of California Davis, the 2021 recipient of the Akira Okubo Prize, and Benjamin Walker, University of Oxford, the 2021 recipient of the H. D. Landahl Mathematical Biophysics Award.
  3. Editorial – Guest editorial on the SMB Mentoring Program by Dr. Shelby Scott titled “The Unexpected Joy of an SMB Writing Group.”
  4. Featured Figures – Highlighting the research by Dr. Mario Banuelos, California State University, Fresno, and colleagues; and the most downloaded paper in Bulletin of Math Biology, August 2021 issue by Dr. Gustavo Nicolás Páez, Myanmar Development Institute, and colleagues.

To see the articles in this issue, click the links at the above items.


Contributing content

Issues of the newsletter are released four times per year in Spring, Summer, Autumn and Winter. The newsletter serves the SMB community with news and updates, so please share it with your colleagues and contribute content to future issues.

We welcome your submissions to expand the content of the newsletter.  The next issue will be released in December 2021, so if you would like to contribute, please send an email to the editors by the end of November 2021 to discuss how your content can be included. This could include summaries of relevant conferences that you have attended, suggestions for interviews, professional development opportunities etc. Please note that job advertisements should be sent to the SMB digest rather than to the newsletter.

If you have any suggestions on how to improve the newsletter and would like to become more involved and/or contribute, please contact us at any time. We appreciate and welcome feedback and ideas from the community. The primary contact editor is Reginald.

We hope you enjoy this issue of the newsletter!

Alys, Fiona, Jacob, Reginald, and Ruth
Editors, SMB Newsletter


News Section

By Dr. Ruth Bowness

In this issue of the News section, we highlight the updates from SMB Subgroups, Bulletin of Mathematical Biology, a new mathematics podcast and upcoming conferences. Read on below.



SMB Subgroups Update

Cell and Developmental Biology subgroup

The SMB CDEV Subgroup is looking to expand its blog post series

(smb-celldevbio.github.io/blog/) by including features from junior researchers, particularly graduate students and postdocs who might be soon looking for their next position. We encourage interested researchers to nominate themselves or nominate someone in their research group who could benefit from this opportunity. We invite you to fill out the form here: docs.google.com/forms/d/e/1FAIpQLSdoSUPsPeWD7f1Nas72msZ1j1KdZGdtJNTz2b37hzmWcIfwXg/viewform to sign up.

Immunobiology and Infection Subgroup

On August 3 and 5, 2021, the Immunobiology and Infection subgroup held a 2-part methods webinar on learning to use Stan, taught by Dr. Christiaan van Dorp (Los Alamos National Laboratory) and monitored by Dr. Jessica Conway (Penn State University). See www.smb.org/forums/topic/stan-webinar-hosted-by-immunobiology-and-infection-smb-subgroup/ for more details.

Mathematical  Oncology subgroup

The Mathematical Oncology subgroup would like to draw members attention to two special issues currently accepting submissions:

  • Networks in Cancer: From Symmetry Breaking to Targeted Therapy
    Journal: Symmetry
    Guest editors: C. Axenie, R. Bauer, M Rodriguez Martinez
    Deadline: February 28, 2022
  • Understanding the Evolutionary Dynamics and Ecology of Cancer in Treatment Resistance
    Journal: Cancers
    Guest editor: D. Basanta
    Deadline: March 31, 2022

Mathematical Neuroscience subgroup

The Mathematical Neuroscience subgroup has ‘some’ new officers:

Chair person: Cheng Ly , cly@vcu.edu , Associate Professor at Virginia Commonwealth University

Vice-Chair person: Pamela Pyzza , pyzza1@kenyon.edu , Assistant Professor at Kenyon College

Advisory member: Chiteranjan Mahapatra , c.mahapatra97@gmail.com , Postdoc at Indian Institute of Technology (Bombay), but soon to be at postdoc at Paris-Saclay Institute of Neuroscience 

Methods for Biological Modeling

The Methods for Biological Modeling subgroup is putting together a special issue for BMB.
Special issue titleData-driven methods for biological modeling
Description: This special issue highlights the development of novel data-driven methods, including statistics, machine learning, parameter estimation, and uncertainty quantification, and combinations thereof, towards modeling biological systems. These newly developed methods will tackle challenges that are commonly encountered when modeling real-world experimental, field, pre-clinical, or clinical data. Examples of such challenges include high dimensionality, computational complexity, observation or process error, model bias, and intra- or inter-individual heterogeneity. Contributions to this special issue require validation of new methods with real-world data or simulated data sets that contain features of real-world data that exemplify an outlined modeling challenge. Papers should include a discussion justifying why the developed method is novel and not an application of previously developed methods, as well as how the method may be broadly applicable across different areas of biology, including medical, ecological, genetics, and epidemiological applications.
If anybody is interested in contributing, please e-mail smbmethodsgroup@gmail.com.

Bulletin of Mathematical Biology

A reminder that you can directly transfer manuscripts from bioRxiv to the Bulletin of Mathematical Biology. See www.biorxiv.org/submit-a-manuscript

Mathematics podcast

A podcast about mathematics and the people who develop it which combines recent developments and visions for the future of the field and creates a virtual hub that highlights ideas, people and research topics in mathematics.


See the latest podcast on ‘Mathematics and Cancer Therapy’, where Trachette Jackson is interviewed by Lynn Brandon.

Upcoming Conferences

Case Comprehensive Cancer Center: Artificial Intelligence in Oncology Symposium
November 8-9, 2021 (online)
Precision Medicine and Cancer Disparities will bring together clinicians, biomedical engineers, computer scientists, executives, thought leaders, and entrepreneurs with expertise in precision medicine, AI, machine learning, and oncology. These experts will discuss technical advances in AI, the challenges and advancements in deploying AI in the clinic, the need for the use of AI to address health disparities, the current regulatory and reimbursement landscape for AI in medicine, and the potential of AI to impact global health.
See case.edu/cancer/events/artificial-intelligence-oncology


SMB Mentoring Program Update

Mentoring Program activities at the annual meeting:
  • Early Career Training Workshop
  • Mentor-mentee matching 
  • Mentoring lunch

Mentoring activities throughout the academic year:



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People Section

By Dr. Fiona Macfarlane







Interview with Professor Michael Savageau, Distinguished Professor in the Departments of Microbiology & Molecular Genetics and Biomedical Engineering at The University of California Davis and the 2021 recipient of the Akira Okubo Prize.







Interview with Dr Benjamin Walker a Postdoctoral Research Associate at the University of Oxford and the 2021 recipient of the H. D. Landahl Mathematical Biophysics Award.




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Editorial Section

By Dr. Shelby Scott 

The Unexpected Joy of an SMB Writing Group

Day 1: three late-stage PhD candidates and a postdoc show up in a Zoom room. We’re all a little nervous and trying to remember exactly which SMB Meeting we met at or who we all have in common from our academic networks. It was June of 2020, the pandemic was ramping up, and it was our first day in a SMB writing group. Since then, these women and I have met every other week to share our triumphs and challenges in the academic sphere, all while providing feedback on our academic writing. What started as strictly providing writing feedback became so much more.

We talked through funding struggles, visa issues, and the isolation of the pandemic. We celebrated draft submissions to journals, shared foster kitten stories, and supported applications to jobs that may have been out of reach. We each have differing personal and academic backgrounds, but those differences make us all the better. One member will always nitpick the word choice and grammar, while one will shake up the entire manuscript structure to improve clarity. Someone else is the queen of all figures and knows just how to tweak positioning to make things cleaner, while someone else is all about the content and citations. This writing group has made me, personally, far more willing to accept feedback from peers, far better at providing feedback to others, and, most importantly, made me feel far less alone while finishing a dissertation mid-pandemic. To the women in my writing group: thank you for getting me here. To those who are considering joining one: do it. You deserve the space to work on your craft without fear of judgment.

Day 480: three postdocs and a health data scientist show up in a Zoom room.


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Featured Figures

By Dr. Reginald L. McGee II and Dr. Alys Clark

Early Career Feature

A recent paper by Dr. Melissa Spence (University of California, Merced), Dr. Mario Banuelos (California State University, Fresno), Dr. Roummel F. Marcia (University of California, Merced), and Dr. Suzanne Sindi (University of California, Merced) entitled “Detecting inherited and novel structural variants in low-coverage parent-child sequencing data” considers computational approaches that leverage sparsity and convex optimization for variant detection within next-generation sequencing data. 


In the work the authors propose a model for predicting inherited and novel genomic structural variants in related individuals. The model simultaneously considers one parent’s (f_p) and one child’s (f_c) genomic signal. It combines relatedness constraints, a sparsity-promoting penalty, and a maximum likelihood approach for detecting these binary variables. The constrained optimization is solved analytically and this approach improves variant detection for both simulated data and real genomic data across multiple generations.

To read more about this exciting work, please see the link: www.sciencedirect.com/science/article/pii/S1046202319300313







Most Downloaded Paper in Bulletin of Mathematical Biology, August 2021 Issue

A recent paper authored by Gustavo Nicolás Páez (Myanmar Development Institute), Juan Cerón and Santiago Cortés (Factored.Ai, Columbia), Adolfo Quiroz (Universidad de los Andes), José  Zea (Instituto Nacional de Salud), Camila Franco (Universidad de los Andes), and Érica Cruz, Gina Vargas, Carlos Castañeda (Instituto Nacional de Salud) has become the most downloaded paper in the August 2021 Issue of the Bulletin of Mathematical Biology. The paper is entitled “Alternative Strategies for the Estimation of a Disease’s Basic Reproduction Number: A Model‑Agnostic Study”.

The article considers strategies for calculating the effective reproduction number in a variety of different contexts. As the reproduction number is used in policy making, particularly in the current context of the covid-19 pandemic, accurate calculation and reporting of reproduction number is important. However, reproduction number calculation based on models relies on the assumptions made in those models, and these assumptions must be carefully considered when deriving and reporting these values from data. The paper assessed four different models (three of them novel) and carefully compared the models and their underlying assumptions. The study showed that no individual model could be considered to be a priori preferable to the others, and recommended that multiple models be employed in studies of disease transmission, with appropriate reporting of assumptions and outcomes, such that experts can adequately interpret the impact of modelling choices on reported reproduction numbers.

To read more about this exciting work, please see the link:






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