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  • Spring 2026 SMB Newsletter

    21 Apr 2026 11:05 PM | Anonymous

    Olivia Chu (Bryn Mawr College), Ryan Murphy (University of South Australia), Ananth Srinivas (LSU Health New Orleans), and Sara Hamis (Uppsala University).

    We apologize for our brief hiatus, but we are back with this Spring 2026 newsletter and some exciting bonus material to come - stay tuned! 
    1. News - updates from: 
    2. People - Interview with Greg Rempala and Hye-Won Kang, chair and vice-chair of the new Reaction Networks subgroup
    3. Editorial - SMB Annual Meeting and engaging with SMB
    4. Featured Figure - Kira Pugh, Uppsala University
    5. In our next issue... 

    To see the subsections of 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 submissions to expand the content of the newsletter.  The next issue will be released in the Summer, so if you would like to contribute, please send an email to the editors by the start of June 2026 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 Member Forum 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 editors can be reached at newsletter@smb.org.

    We hope you enjoy this issue of the newsletter!

    Olivia, Ryan, Ananth, and Sara
    Editors, SMB Newsletter

    News Section

    By Olivia Chu

    In this issue of the News section, we highlight the updates from the Bulletin of Mathematical Biology (BMB) and our SMB Subgroups. Read on below.

    From BMB

    • Did you know that publishing in the Bulletin of Mathematical Biology (BMB) provides financial support to the SMB? Learn how in the Bulletin's editorial article, available here.

    SMB Subgroup Updates

    Reaction Networks

    As a newly established subgroup within the Society for Mathematical Biology (launched in January of this year), we wanted to highlight a few items—particularly since this is our first opportunity to communicate with the broader SMB community.

    We have several upcoming activities:

    • As part of introducing the subgroup, we note that we are organizing multiple minisymposia at the 2026 SMB Annual Meeting (joint with ECMTB in Graz), highlighting recent advances in reaction network theory and applications.
    • We would also like to highlight the upcoming CRNT 2026 conference at the University of Hawaii (May 17–22, 2026), which will be of strong interest to our community
    • In addition, we have just launched our official subgroup website, which provides information on our scope, activities, and resources:

    We are very much looking forward to growing the subgroup and contributing to SMB activities in the coming years.

    Immunobiology and Infection

    The IMMU subgroup is excited to announce the results of our most recent elections. Jason Shoemaker, University of Pittsburgh, was elected as subgroup Chair and Tin Phan, Los Alamos National Laboratory, was elected as subgroup Secretary. Congrats to both! Jason and Tin will start their terms at the upcoming annual meeting. Keep a look out for announcements about IMMU social activities in Graz.

    Mathematical Oncology

    • Call for Co-Chair Self Nominations: The terms of two of the three Mathematical Oncology Co-Chairs expire this summer. An election will be held to identify two new co-chairs to serve alongside Rebecca Bekker. If you are interested in serving as MathOnco co-chair from 2026-2028, you can self-nominate here. Nominations will be due by Friday, April 24th. 
    • The Mathematical Oncology Subgroup is pleased to announce its inaugural annual awards for outstanding early career researchers. These awards will recognize exceptional work at the graduate and postdoctoral levels (or equivalent) within the field of mathematical oncology. Details, including the self-nomination form, are available at: Mathematical Oncology - Call for Award Nominations. If you are an earlier career researcher giving a talk (in a mini-symposium or a contributed session) at the 2026 Annual Meeting in Graz, we encourage you to apply. If there is a member of your group who fits the criteria, please encourage them to apply! The deadline is Friday, May 1st. 

    Upcoming Annual Meeting

    The Annual Meeting, held jointly by SMB and ESMTB, will take place July 13-17, 2026 at the University of Graz in Austria. For more information, see the conference website. 

    Note that early bird registration ends on April 30th! 

    Check out Ananth Srinivas's Editorial about the annual meeting below. 

    People Section

    By Sara Hamis

    Read our interview with Professors Greg Rempala (The Ohio State University) and Hye-Won Kang (UMBC), the chair and vice-chair of the newly-finalized Reaction Networks subgroup. 

    Editorial

    By Ananth Srinivas

    Upcoming Annual Meeting

    Read Ananth's Editorial on the SMB Annual Meeting, all it offers, and what it means to the SMB community here.

    Engaging with SMB

    Featured Figure

    By Ryan Murphy

    In this issue, we feature the work of Kira Pugh and colleagues in their recent article A bibliometric study on mathematical oncology: interdisciplinarity, internationality, collaboration and trending topics.

    Dr. Pugh tells us more about the article below:

    In this study, we take a step back and look at mathematical oncology from a science-of-science perspective. Specifically, we use bibliometrics—the statistical analysis of publication metadata—to study how the field has developed over time. We were especially motivated to do this because, while there are many excellent literature reviews of mathematical oncology, there are few bibliometric studies. As a result, there is limited quantitative understanding of how the research field and community have evolved. Such insights can, for example, help inform research communication, funding allocation, and education strategies.

    To ground our work in mathematical biology, we identify journals that have consistently published mathematical oncology research and collect publication metadata from bibliographic databases. We then investigate interdisciplinarity, international collaboration, and trending topics through discipline-based citation flows (left panel), global author connectivity (middle panel), and word frequencies (right panel).

    Our results demonstrate that mathematical oncology has changed substantially since the 1960s, becoming more internationally connected, more collaborative, and more diverse in the topics it studies. The field remains strongly interdisciplinary, interacting closely with the life sciences while continuing to be cited in mathematics journals. In this sense, paraphrasing Reed (2015), our results suggest that mathematical biology is good for both the biological and mathematical sciences.

    In our upcoming issues... 

    • Get to know our new Newsletter editors
    • Learn more about NITMB, the National Institute for Theory and Mathematics in Biology, funded by the Simons Foundation and the National Science Foundation (NSF)
    • Read about research, teaching, and mentoring activities at small liberal arts colleges (SLACs) and primarily-undergraduate institutions (PUIs) 


  • BMB Article Highlight: Hsuan-Wei Lee (2025)

    20 Apr 2026 1:55 PM | Anonymous

    Phase Boundaries and Critical Transitions in Coupled Epidemic–Behavioral Systems

    by Hsuan-Wei Lee

    Read the paper

    We introduce a spatial epidemic-behavioral model coupling SIS dynamics with evolutionary game theory to investigate voluntary isolation behaviors. Comprehensive exploration of four-dimensional parameter space (transmission, recovery, infection costs, isolation costs) reveals eight robust equilibria separated by sharp phase boundaries. Critical thresholds govern abrupt transitions between cooperation and defection regimes. A striking paradox emerges: intense cross-infection coupling drives near-universal isolation adoption yet paradoxically sustains persistent endemic infection, demonstrating that widespread cooperation does not guarantee epidemic control. The system exhibits extreme sensitivity characteristic of critical phenomena.


    Phase Boundaries and Critical Transitions in Coupled Epidemic–Behavioral Systems


  • Biology in Numbers - Episode 3.6: Daniel Cruz

    17 Apr 2026 4:44 PM | Anonymous

    …where we talk multi-scale models, community building, and peanuts in cereal.

    Daniel is an immigrant from Ecuador who got his Ph.D. in Mathematics in 2019. He had two postdoc positions prior to joining the faculty at Cal Poly SLO. Outside of research & teaching, Daniel engages in community building.

    Learn more about Daniel’s research and teaching on his website: https://sites.google.com/view/dcruz




    Find out more about SMB on: 

    Apple Link      Spotify Link     Read the full transcript


  • BMB Article Highlight: Antonio Palacios et al. (2026)

    16 Apr 2026 1:11 PM | Anonymous

    Disorder and Homeostasis in ANIBOT. A Biologically-Inspired Animal Robot

    by Kevin Castillo, Madeline Parker, Nathan Reyes, Antonio Palacios, Erin C. McGee, Patrick Longhini, Horacio Lopez, and Kevin Vo

    Read the paper

    The effects of external perturbations (or disorder) in the Hopf bifurcations of a central pattern generator (CPG) network of neurons that serves as a model for the circuit realization of ANIBOT--a biologically-inspired animal robot with four legs--are studied, analytically and computationally, from the standpoint of homeostasis. Recent developments in the mathematical description of homeostasis, are employed to explore the CPG response to perturbations of the network connectivity, the internal dynamics of the neurons, and electronic noise. The results show that except for the Walk and Jump gaits, the phase dynamics of all other gaits (Walk, Jump, Trot, Bound, Pace, and Pronk) exhibit perfect homeostatic responses.


    Homeostasis in Animal Gaits

  • BMB Article Highlight: Ana María Portillo et al. (2026)

    10 Apr 2026 5:31 PM | Anonymous

    A mathematical model to simulate the biological action of Infliximab on TNF-alpha in patients with Inflammatory Bowel Disease: the critical role of drug clearance

    by Ana M. Portillo, Ángel de Prado, Ana J. Soares

    Read the paper

    We develop a mathematical model designed to balance biological realism with analytical simplicity, that still retains essential clinical features. The model integrates clinical and pharmacokinetic factors to simulate TNF- dynamics and infliximab action with only four equations and few parameters. 1. We establish key mathematical properties of the model, thus providing a rigorous framework supporting biological interpretations. 2. We present numerical simulations illustrating the model’s dynamical behaviour under relevant biological scenarios and exploring different therapeutic conditions. 3. Our model identifies infliximab clearance as a key determinant of therapeutic efficacy.


  • BMB Article Highlight: Eberhard O. Voit (2026)

    02 Apr 2026 5:29 PM | Anonymous

    Format-Preserving Reduction of Canonical Nonlinear Models

    by Eberhard O. Voit

    Read the paper

    New experimental techniques in biology have been generating unprecedented amounts of data. These offer new opportunities for analysis, including the design, analysis, and application of computational models, which are usually formulated as systems of differential equations. While this trend is very welcome, it brings with it challenges associated with technical and conceptual aspects of the models and their analysis. The article proposes methods for reductions in the size of models that approximately retain their dynamical responses. These approximations are often so good that errors are within the range of experimental uncertainty. The proposed methods are hoped to tame some of the challenges associated with increasingly larger models.


    Reduction of a Model of White Rot Fungus


  • Biology in Numbers - Episode 3.5: Gary An

    27 Mar 2026 5:26 PM | Anonymous

    …where we talk physician-scientists, sepsis and making your own dragon head.

    Dr. An is a clinically active trauma/critical care surgeon who also does computational research that integrates high-resolution agent-based models with ML and AI to study inflammatory processes such as sepsis and wound healing.

    He also likes considering sandwiches in abstraction.

    Find out more about Gary and his work on his website:

    Website: https://www.medicaldigitaltwins.ai/



    Find out more about SMB on: 

    Apple Link      Spotify Link     Read the full transcript

  • BMB Article Highlight: Weiming Wang et al. (2026)

    24 Mar 2026 4:12 PM | Anonymous

    Stochastic Modeling and Optimal Control of HIV-1 Infection Dynamics Under Combination Antiretroviral Therapy

    by Yiping Tan, Suli Liu, Yongli Cai, Xiaodan Sun, Ruoxia Yao, Daihai He, Zhihang Peng, and Weiming Wang

    Read the paper

    Within-host HIV-1 dynamics under cART exhibit persistent fluctuations driven by environmental noise. We develop a stochastic differential equation model to show that this noise decisively influences viral suppression versus persistence. Through optimal control theory, we compare strategies of cART intensification, immune modulation, and their combination. A cART-dominated, immune-assisted approach proves most effective, ensuring rapid viral suppression and cost-efficiency. This study offers a theoretical framework for optimizing HIV-1 treatment protocols.


    Stochastic Modeling and Optimal Control of HIV-1 Infection Dynamics Under Combination Antiretroviral Therapy


  • BMB Article Highlight: Ashley Scruse et al. (2026)

    17 Mar 2026 3:30 PM | Anonymous

    Counting Subnetworks Under Gene Duplication in Genetic Regulatory Networks

    by Ashley Scruse, Jonathan Arnold, and Robert Robinson

    Read the paper

    Gene families help us understand how gene regulation evolves. While sequence evolution is well-studied, regulatory evolution is not. Members of gene families form genetic regulatory networks (GRNs) where gene A regulates gene B. We develop a model counting regulatory subnetwork motifs within gene families as they evolve through duplication. The result is a count |M(n)| of how these motifs evolve to a stage with n total genes. The key parameter is the probability that a regulatory relation is preserved when a gene is duplicated. For Full Duplication, the mean and variance of motif counts can be computed exactly, enabling significance tests to identify targets for directed evolution. Partial and Mixed Duplication models are also presented.


    This graphical abstract illustrates the mathematical framework for counting subnetwork motifs in genetic regulatory networks (GRNs) under gene duplication. The left panel depicts the gene duplication process: before duplication, gene A regulates gene B; after duplication of B, the duplicate gene B' may inherit the regulatory relationship from A with probability π. The right panel presents the key analytical results for the Full Duplication model (π = 1), including closed-form expressions for the expected motif count E(|M|) and the second moment E(|M|²). The bottom section shows the statistical framework for identifying significant motifs, with formulas for variance and Z-score calculation, along with a workflow for applying these methods to identify targets for directed evolution. The paper also derives analogous results for Partial Duplication (0 ≤ π ≤ 1), where the inheritance probability vector π = (π₁, ..., πₖ) allows each gene family to have its own probability of inheriting regulatory relationships, and discusses the Mixed Duplication model, where with probability 1−q all regulatory links are retained and with probability q each link is retained independently with probability p. See the full article for these additional duplication models.


  • Biology in Numbers - Episode 3.4: Ranjini Bhattacharya

    24 Feb 2026 9:59 AM | Anonymous

    ...where we talk forging cancer cells, science policy and dancing.

    Ranjini is a final-year PhD student in the IMO Department at Moffitt Cancer Center. She uses evolutionary game theory to study cancer foraging. Outside of her research, Ranjini engages in science communication and science policy with non-expert audiences, and loves to engage her creative side.

    You can connect with her on Linkedin.


    Find out more about SMB on: 

    Apple Link      Spotify Link     Read the full transcript

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