Conferences  >  Life Sciences  >  Systems Biology and Computational Biology

ICERM

The field of mathematical and computational biology is rapidly growing. The most applicable computational models have been developed in collaboration between computational and life science researchers. This workshop aims to bring these groups together to facilitate and promote collaborations among them. A mathematical model for one disease might also be useful in modeling another disease. Some researchers are working on theoretical mathematical & statistical problems related to biological and biomedical applications, while others are developing computational methodologies to address fundamental life science knowledge gaps. This workshop fosters and features collaborations among these groups along with experimentalists and physicians. Theoreticians will be exposed to a variety of open biological questions in need of state-of-the-art and efficient mathematical methods. Computational scientists will learn about more robust and efficient methods that could be tailored to answer biological problems.

Program Staff;     Phone: [1-401-863-5030];     Email: programstaff@icerm.brown.edu

Biomath 2023 is devoted to recent research in life sciences based on applications of mathematics as well as mathematics applied to or motivated by biological studies. It is a multidisciplinary meeting forum for researchers who develop and apply mathematical and computational tools to the study of phenomena in the broad fields of biology, ecology, medicine, biophysics, biochemistry, pharmacokinetics, chemoinformatics, biotechnology, bioengineering, environmental science, etc.

Applied Mathematics (in general),    Genomics and Bioinformatics

European Molecular Biology Organization – EMBO

Biology,    Molecular Biology

Institute for Molecular Genetics and Genetic Engineering

The Belgrade Bioinformatics Conference (BelBi2023) is scheduled for June 19-23, 2023, in Belgrade, Serbia, as a hybrid event. This five-day conference will include keynote and invited talks by experienced experts, oral and poster presentations, and workshops. The main goal of the BelBi conferences is to foster contacts between scientists to share experiences, disseminate the latest information on advances in their fields, gain and increase the visibility of their research, and bring young researchers together with peers and senior colleagues. We sincerely hope that BelBi2023 will serve as an international platform for researchers from around the world to meet, initiate new collaborations, and expand professional contacts. We look forward to welcoming you to Belgrade for this inspiring conference!

Email: info@belbi.bg.ac.rs

Biological Data, Biomedical Informatics, Theoretical Approaches to Bioinformation Systems (TABIS)

Genomics and Bioinformatics,    Neural Networks and Artificial Intelligence, Machine Learning

European Molecular Biology Organization – EMBO

Biology,    Oncology

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Cells are the fundamental building blocks of life. Recent advancement in biotechnology has allowed us to peek inside this every cell for better understanding of biology and human disease. Single-cell technology also generates big and complex data and brings about new data science challenges for computational and life scientists. The objective of this workshop is to bring together international leaders in diverse disciplines including mathematical, statistical, computational, biological and medical in a collaborative atmosphere to develop the collaborative capacity that will tackle various underlying data science challenges in single-cell research.

Molecular Biology,    Scientific Computing and Data Science

Isaac Newton Institute for Mathematical Sciences (INI)

The aim of this summer school is to foster the development of a community of quantitative scientists who, while working on different application areas, share their knowledge and help address fundamental questions in the mathematics of movement. The goal is to identify common challenges and cross-fertilise concepts and techniques for modelling and analysing movement data in animal ecology and cell biology. With basic, as well as advanced, topics on the mathematics of movement the summer school welcomes early career researchers who that are new novice to the area but also those who that are already familiar with it. The first three days will be dedicated, respectively, to (i) Data Acquisition and Technology, (ii) Data Analysis, and (iii) Modelling, while the 4th and 5th days will be spent working in separate groups on specific dataset and modelling challenges. There will be sessions for early career presentations and poster sessions, as well as opportunities to hear about successful interdisciplinary collaborations and various activities to enable networking with the programme organisers and the many academic participants of the programme. There will also be a competition for the best poster.

Modeling and Simulation,    Courses and Events for Math Students and Early Career Researchers

Recent progress in biology has led to an explosion of factual knowledge about the living world over a huge range of scales in space and time. Yet, many questions about how to make sense of this data remain across the entire diversity of the living world from the smallest bacterium to the ecosystems of the Serengeti. This meeting aims to bring together a diverse collection of researchers interested in finding ways to parlay this ever-increasing factual knowledge into a corresponding array of conceptual knowledge. The goal of this symposium is to assemble an interdisciplinary community and to provide a platform to discuss perspectives on the role of theory in biology, and importantly also vice versa, the impact that biology can have on theory.

Biology,    Molecular Biology

European Molecular Biology Organization – EMBO

Biology,    Molecular Biology

Kavli Institute for Theoretical Physics, University of California, Santa Barbara

During animal and plant development, cells self-organize into complex organisms, through the gradual refinement of cellular identities and their arrangement in space. This is an iterative process, which progresses through successive rounds of symmetry breaking, accompanied by changes in molecular and mechanical properties that feed back across multiple scales. Many of the elementary processes underlying developmental patterning and morphogenesis are now well documented, and a growing array of tools is available to observe and manipulate their dynamics. Yet, we lack a set of general principles that explain how they are coordinated in space and time to produce a defined outcome, and comprehensive synthetic approaches that use such principles to recapitulate development in vitro. This program will bring together experimentalists and theoreticians to work towards an integrated view of self-organization. This requires that we examine how the collective dynamics of development emerge from individual cellular behaviors - how cellular decisions in high-dimensional gene expression landscapes are coordinated in patterning, and how cellular force generation and mechanical feedbacks provide a substrate for tissue-scale communication and morphogenesis. Unifying these different processes, the notion of information may provide a common currency for the molecular and mechanical cues that guide development, encouraging us to consider that information is not only conveyed and interpreted but also self-organizes.

morphogenesis, development, plant development, self-organization, theory, quantitative biology, biophysics

Biophysics, Medical Physics,    Biology

Isaac Newton Institute for Mathematical Sciences (INI)

Modelling collective group movement in animal ecology and cell biology has, over the years, followed two relatively parallel modelling paths. Most prevalent for the former are what one might define as discrete level models, whereby computational constructs are used to keep track of the spatio-temporal dynamics of each individual in a group. Problems in the latter, cell biology, have been tackled mostly by continuous models whereby the details of the individuals are neglected, in favour of a description of the entire population through, e.g. a density function. However, more recently hybrid agent-based/population models have gained increasing usage.

As the overall aim of the workshop is to create an overarching modelling framework with which to interpret common empirical features, the exchange of ideas and techniques from the different communities is an invaluable opportunity to move forward and at the same to delineate the boundaries of applicability of the different approaches in collective movement research.

Modeling and Simulation,    Applied Mathematics (in general)

European Molecular Biology Organization – EMBO

Any adequate theory of evolutionary change must cover both the sources and the consequences of phenotypic variation. On the one hand, we must understand the various processes—genetic, metabolic, physiological, developmental, and behavioral—that generate variation. On the other hand, we must understand the sorting processes that lead to the differential survival of different variants. The latter aspect is covered by traditional evolutionary genetics, with its well-developed set of concepts and models. In contrast, there seems to be no overarching theory or unifying framework able to explain the enormous diversity of processes generating variation. These processes are not only dauntingly complex, but also occur at many different levels of organization—from the molecular to the cellular, tissue, organ, organismic, and even supra-organismic levels (ecological or social). We could conclude from this that no theory of the sources of variation is possible, or we could call for a novel, empirically grounded, organismic systems biology that integrates philosophical, mathematical, and experimental approaches to tackle the issue. We will look at this project from a broad theoretical vantage point to assess the future of evolutionary and developmental systems biology.

Biology,    Molecular Biology

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

The advances in imaging techniques have enabled the access to 3D shapes present in a variety of biological structures: organs, cells, organelles, and proteins. Since biological shapes are related to physiological functions, biomedical analyses are poised to incorporate more morphological data. For example, at the macroscopic scale, characterizing brain morphologies allows clinicians to quantify the progression of Alzheimer's disease. At the microscopic scale, the characterization of protein morphologies allows biologists to understand how these biomolecules react to chemical variations of their environment and helps detect promising pharmacological targets for the treatment of conditions ranging from neurological disorders to several cancers. Therefore, different biological scales ask a common statistical question: how can we build mathematical and statistical descriptions of biological morphologies and their variations? This workshop invites participants from different application fields to exchange mathematical and statistical methods for the study of biological shapes.

Pattern Recognition and Image Processing, Machine Vision,    Biophysics, Medical Physics

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

The interface between biology and quantitative disciplines including physics, mathematics and engineering is rapidly expanding. This is the result of many factors, but is largely driven by higher resolution spatial and temporal data from cutting edge imaging techniques, and increasing success in applying physical modeling techniques to biological problems. Mechanobiology is an especially rapidly developing field at the quantitative biology interface. This field describes how force is generated in biological systems, how force impacts chemistry, and how force generation is controlled by intracellular signaling pathways. Numerous feedforward and feedback interactions connect forces in cells to the dynamics of proteins and gene expression, resulting in highly nonlinear systems with complex and often non-intuitive behaviours.

Biophysics, Medical Physics,    Computational Physics and Numerical Simulation

Isaac Newton Institute for Mathematical Sciences (INI)

The study of interactions among living entities covers broad scientific domains, ranging from molecules and cells through individual organisms and groups to species, populations and communities. Common to all domains is the need to quantify the presumed interactions at the relevant spatial and temporal scales. While no formal theory exists in the literature, there exist different approaches that aim to construct a mechanistic representation of how individuals interact with each other as well as how to measure such interactions, but in most cases such approaches are specific to the problem at hand. The common factor among the existing approaches is their intention to represent the sequential nature of how organisms interact, first acquiring information from their surroundings, then processing that information and subsequently selecting a movement response.

By cross-fertilising different ideas and techniques in animal ecology and cell biology we aim to gain a more realistic perspective on measurement and representation of organism interactions, revisiting existing concepts, and permitting new discoveries and insights.

Modeling and Simulation,    Applied Mathematics (in general)

The ReSOLUTE-IMI Consortium

The RESOLUTE and REsolution consortia of the Innovative Medicines Initiative of the European Union have been empowering over the last years the scientific community with novel research tools and datasets for transporters of the Solute Carrier (SLC) supergroup. In 2023, both projects are coming to an end, and we would like to finish with a big celebratory and future-looking conference: “Unlocking Transporters for Drug Discovery”. At the event expect to see presented the results and lessons learned by the RESOLUTE and REsolution consortia over the last five years. Furthermore, top international scientists interested in metabolism and its regulation, drug discovery, the function and structure of membrane proteins will be speaking.

RESOLUTE Communications Manager;     Email: contact@re-solute.eu

transporters, solute carriers, SLC, genomics, metabolomics, proteomics, systems biology, data integration, drug discovery, medicine, variants, mutants, structural biology, resources, bio-tools, cell lines, plasmids

Molecular Biology,    Genomics and Bioinformatics

Isaac Newton Institute for Mathematical Sciences (INI)

Modeling and Simulation,    Applied Mathematics (in general)

Centre de recherches mathématiques (CRM)

While brain function originates in neuron, its energy is supported by the vascular system. With the recent development of anatomically detailed synthetic network models of the entire cerebral circulation, it is now possible to perform detailed simulations of physiology in realistic brains of small animals and humans on the computer. Modeling microcirculatory blood flow as a biphasic suspension of red-blood-cell and plasma, blood pressure, flow and hematocrit can be simulated in whole brains on the computer. Combining Poiseuille’s hemodynamic simulations with advection/diffusion equations describing oxygen diffusion, the human brain metabolism can now be modeled in-silico, by integrating tissue oxygen consumption and differential equations describing compartments associated with neural and glial brain cells. In parallel, energy metabolism regulation in the brain and its modeling has greatly progressed over the past few decades. This workshop will thus be focused on digital human brains, and their use to predict critical metabolic functions namely blood flow, oxygen extraction and cellular metabolism across all length scales down to the level of individual capillaries and cells. Courses and conferences will be combined with research presentations and practical workshops.

Modeling and Simulation,    Applied Mathematics (in general)

CIRM – Centre International de Rencontres Mathématiques

Ecology, epidemiology and evolution

Isaac Newton Institute for Mathematical Sciences (INI)

The purpose of this workshop is to bring together scientists interested in different areas of complex movement in a biological context, from field research, to data analysis, to theoretical modelling. In particular, the focus will be on complex movement beyond the Markov property, such as memory-dependent animal foraging processes, spatial avoidance due to past deposition of animal scent or resource depletion, and directed motion in neutrophils. Despite its ubiquity, the mathematical difficulty in dealing with history dependence has hampered the study of non-Markov movement processes. Past empirical limitations are also responsible for the lack of a general theory to describe history dependent movement processes, as detection of features that would distinguish between Markov and non-Markov model predictions were not attainable. Currently, movement data may reach unprecedented resolution, and there is a renewed interest in developing non-Markov movement models, exemplified by recent theoretical studies to devise general prescriptions to simulate non-Markov stochastic processes.

Modeling and Simulation,    Applied Mathematics (in general)

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

What have we learned from the COVID-19 pandemic, and how can we be better prepared for the next global outbreak? This workshop brings together collaborative teams of modellers, statisticians, epidemiologists, genomics experts, public health decision-makers, and those implementing and delivering interventions who have been working together in a research network, aiming to increase Canada’s capacity for data-driven emerging infectious disease modelling to directly support future public health decisions. This BIRS meeting is an important opportunity for network members and collaborators to share the outcomes of their research over the two years since the network was launched with funding from the federal government. The questions being tackled at this workshop are grounded in public health needs and generated in partnership between research investigators and knowledge users – public health leaders, health administrators and policy-makers.

Modeling and Simulation,    Epidemiology & Public Health

Centre de recherches mathématiques (CRM)

While network models have been studied as independent systems, efforts in neuroscience in recent years has been put towards inferring networks of the brain from imaging data. Using probabilistic methods and inverse models, recurrent networks across populations and their change with disease have been characterized based on input from electrophysiological and functional imaging.

This sub-theme will cover the notions of network dynamics, discuss conceptual frameworks to model brain network topology and provide the latest progress in neural network inference from imaging data and associated methodological approaches at modeling networks of the brain.

European Molecular Biology Organization – EMBO

European Molecular Biology Organization – EMBO

Biology,    Molecular Biology

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Fields Institute

This workshop aims to showcase the state-of-the-art mathematical and computational models that are in use in mathematical oncology, with a particular focus on the fourteen hallmarks of cancer. New modeling challenges arise from these hallmarks. Some of the hallmarks relate to the characteristics of the cancer cells themselves (sub-cellular and cellular level), while others include more global effects such as blood circulation, the immune response, the effect and role of the microenvironment, mechanical forces, and the microbiome. Matching the biological diversity of the cancer hallmarks, is the diversity of mathematical approaches and techniques that have been used and are in use to give insight into the growth and spread of cancer – for example, continuum and discrete models; ordinary and partial differential equation models; individual-based and agent-based models; hybrid models; deterministic and stochastic approaches; analytical and computational approaches. Many of these processes act on very different spatial and temporal scales. Hence a new integrated multiscale mathematical modeling framework is needed to include new aspects and insights, such as spatial stochastic models and local and non-local partial differential equation models.

Oncology,    Modeling and Simulation

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Courses and Events for Math Students and Early Career Researchers,    Epidemiology & Public Health

Fields Institute

This workshop aims to take a closer look at how mathematical and computational models can help answer clinically relevant questions and enhance multimodal treatments. Currently, a wide range of modelling approaches study cancer and have a crucial role in treatment delivery from answering questions related to cancer biology and treatment efficacy to directly helping with treatment delivery. In this workshop, we would like to bring together clinicians, biomedical experts, experimentalists, and mathematicians to explore some of the relevant questions on multimodal treatment modelling, efficacy, optimization, drug resistance and clinical delivery.

Oncology,    Modeling and Simulation

Fields Institute

This workshop explores research in methods aimed at connecting mathematical models of cancer evolution and clinical data. It focuses on ecology and evolution of cancer. Traditionally, ecology and evolution have been the most “mathematical” (and perhaps the first mathematical) areas of biology. Mathematical contributions to these fields made in the 20th century are now fundamental parts of scientific knowledge. More recently, methods of ecology and evolution have found their way into oncology, bridging traditional molecular biology and mathematics including stochastic processes, dynamical systems, and nonlinear partial differential equations. New biological challenges lead to difficult mathematical problems and beautiful solutions, which are both innovative mathematically and impactful from the point of view of public health. These will be the focus of the proposed workshop .

Oncology,    Modeling and Simulation

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Courses and Events for Math Students and Early Career Researchers,    Geometry and Topology

Fields Institute

Immunotherapies have revolutionized treatments for several types of cancers, but have been met with clinical trial failures in others. The idea of eliciting an immune response against a tumour is old, but we are only just beginning to harness the potential of the immune system to treat both solid and liquid tumours. To improve immunotherapeutic approaches requires understanding how the immune system interacts around and within a tumour, allowing us to establish effective immunotherapeutic protocols. Mathematical modelling can help identify the mechanisms at the heart of immunotherapeutic efficacy and design successful therapeutic regimens. Close collaboration between experimentalists, clinicians, and quantitative researchers in academia and industry is required to forward models for implementation. This workshop will focus on tightening the links between researchers in different fields to fuel immunotherapy success.

Oncology,    Modeling and Simulation