Trends in Biomathematics: Modeling Cells, Flows, Epidemics, and the Environment

Rubem P. Mondaini is President of the BIOMAT Consortium/International Institute for Interdisciplinary Sciences and a Full Professor of Mathematical Biology and Biological Physics at the Federal University of Rio de Janeiro, Brazil. He holds a PhD in Theoretical Physics from the Brazilian Centre for Physical Research, Brazil. His research activities abroad include a period as a Visiting Scientist at the International Centre for Theoretical Physics (ICTP), Trieste, Italy (1978) and as a Senior Postdoc at the Department of Mathematics of King's College, University of London, UK (1986). He was also a Visiting Professor at the Centre of Physics of Condensed Matter, Lisbon, Portugal (1986) and at the Department of Chemical Engineering of Princeton University (2008). He has been the Chairman of the Annual BIOMAT Conferences since their inception during the BIOMAT 2001 Symposium in Rio de Janeiro, Brazil.

Evolutionary adaptation of the permanent.- A more realistic formulation of herd behavior for interacting populations.- On network similarities and their applications.- impacts of infections and predation on dynamics of sexually reproducing populations.- Global analysis of a cancer model with drug resistance due to microvesicle transfer.- Contact vaccination study using edge based compartmental model (ebcm) and stochastic simulation an application to oral poliovirus vaccine (OPV).- The Effect of Inhibitory Neurons on a Class of Neural Networks.- Pipette Hunter 3D: Fluorescent Micropipette Detection.- Delay Linear Chains in Mathematical Biology: Migratory Birds, Stem Cell Maturation, and Intracellular Chlamydia Infection.- Normalization of a periodic delay in a delay differential equation.- Competition between two tufted C4 grasses: a mathematical model.- Mathematical description of systemic and microcirculations.- The statistical analysis of protein domain family distributions via jaccard entropy measures.- Theoretical and numerical considerations of the assumptions behind triple closures in epidemic models on networks.- Recognition of protein interaction regions through time-frequency analysis.- Using a stochastic sir model to design optimal vaccination campaigns via multiobjective optimization.- Optimal control analysis of HIV-TB Co-infection model.- A prey-predator model with pathogen infection on predator population.- On an invasive species model with harvesting.- Generalized linear models to investigate cyclic trends.- Assessing the effects of holling TYPE-II treatment rate on HIV-TB co-infection.- Discrete and continuum models for the evolutionary and spatial dynamics of cancer: a very short introduction through two case studies.- Modelling therapeutic vaccines.- modeling the genetic code: P-ADIC approach.