Dynamic modeling and statistical inference in the life sciences: philosophical and practical perspectives


Mathematical modeling of living systems brings together the exact and life sciences, borrowing from everything in between and dragging in several disciplines: mathematics, statistics and machine learning, physics, chemistry, complex systems, bioinformatics, experimental design, genomics, systems biology, molecular biology, as well as the interfaces between them.

This complex multidisciplinarity has several implications from the perspective of research programs and training of scientists: it is usually impossible to fit the science into a well-defined field with experts trained in all of its aspects. This observation begs the philosophical question: How to go about studying highly complex systems at a multidimensional interface of fields?

The objective of this course is twofold:

  1. To present a historical and philosophical perspective of modeling life as something that requires thinking about how living systems are built and how we describe them;
  2. Introduce formulations (e.g. dynamic models), frameworks (e.g. Bayesian inference; data treatment), tools (e.g. Python/R packages), and approaches (e.g. understanding some types of experimentation or observation; designing experiments) that allow scientists anywhere in the Mathmematics-Biology spectrum (including the extremes) to practice model-based inference of living systems.

This audience in this course ranges from bench biologists interested in using mathematical models, to mathematicians or statisticians interested in getting involved in the design of experiments for a truly collaborative and applied mathematics. The course is ideal for Early-Career Researchers (students and early postdocs), but also later-career investigators who would like to expand their scientific perspectives.


For all participants, the only requisite for this course is being interested in interdisciplinary research along the Mathematics-Biology axis. For researchers with a PhD an additional recommendation is having some tolerance for being outside of your comfort zone.


Two (2) travel grants are available to participants who would like to attend in person, do not reside in the area, and cannot cover the costs of travel and accommodations. Participants interested should write a 1-2(max) paragraph justification for their request. Award will be judged on the basis of (i) financial need [no specific funding for this purpose], (ii) stage of career [earlier career researchers will be prioritized], (iii) general interest and fit [this criterion will be used only as a a tie breaker if i and ii are equivalent].


Organizers: Caetano Souto-Maior (BCAM), Daniele De Martino (Biofisika Institutua), Miguel Aguilera (BCAM)

Speakers: Johannes Jaeger (Complexity Science Hub, Austria), Veronica Grieneisen (Cardiff University, UK), Kepa Ruiz-Mirazo, Jose M.G. Vilar (Biofisika Institutua, UPV/EHU), Ivan Coluzza (BCMaterials), Daniele De Martino (Biofisika Institutua), Miguel Aguilera (BCAM), Caetano Souto-Maior (BCAM)