NOTE: this page is written and maintained by Eduardo Sontag (eduardo.sontag@gmail.com) 
Current year seminars
CQB Seminar: Tuesday April 25th 2017 12:00 pm, Chang Chan, Cancer risk prediction in mice and humans with germline p53 mutations
The Rutgers Center for Quantitative Biology is pleased to announce the following seminar: Speaker: Chang Chan, CINJ When: Tuesday April 25th 2017 12:00 pm Where: Hill 260 (Busch Campus, Rutgers) Title: Cancer risk prediction in mice and humans with germline p53 mutations Abstract: P53, a tumor suppressor gene, is the most commonly mutated gene occurring in half of all cancers. Germline p53 mutations predispose mice and humans to a high risk of getting a wide spectrum of tumors with a lifetime risk of getting cancer greater than eighty percent. Yet, genetically identical mice with the same p53 mutation will get tumors with a wide distribution of age as well as tumor types. We observe a similar disparate phenotype in a pair of human identical twins who have germline p53 mutation. We present a probabilistic model using epidemiological data to show how stochasticity can produce much of the heterogeneity in phenotypes. Moreover, the model provides insights into the process of tumorigenesis with germline p53 mutations. We use these insights to address the mutational landscape of a set of tumors from human and mice with germline p53 mutations. Lastly, we discuss what is needed to improve predictive models for cancer risk. 
CQB Seminar: Tuesday April 18th 2017 12:00 pm, Yannis Androulakis, interacting biological rhythms
The Rutgers Center for Quantitative Biology is pleased to announce the following seminar: Speaker: Ioannis (Yannis) P. Androulakis, Rutgers Biomedical Engineering When: Tuesday April 18th 2017 12:00 pm Where: Hill 260 (Busch Campus, Rutgers) Title: Modeling of interacting biological rhythms Abstract: In this talk we will review some of our recent work focusing on challenging issues related to the modeling of biological rhythms and their implications on health. The discussion will explore emerging properties of interacting oscillating systems and discuss the implications of the harmonious integration of cascades of oscillators. We focus on the interactions between photoperiod, the HPA, peripheral clocks and cell cycle and their implication on the inflammatory response. We will conclude with a discussion of critical challenges and interventional opportunities targeting the realignment of circadian rhythms. 
CQB Seminar: Tuesday April 11th 2017 12:00 pm, Nastassia Pouradier Duteil
The Rutgers Center for Quantitative Biology is pleased to announce the following seminar: Speaker: Nastassia Pouradier Duteil, Rutgers Camden When: Tuesday April 11th 2017 12:00 pm Where: Hill 260 (Busch Campus, Rutgers) Title: The role of diffusion, growth and cell movement in the spatiotemporal dynamics of EGFR activation Abstract: The development of an organism is controlled by morphogens, signaling molecules diffusing in the organism and acting on cells to produce local responses. Growth is thus determined by the distribution of such molecules. Meanwhile, the diffusion of the morphogens is itself affected by the changes in shape and size of the organism. In other words, there is a complete coupling between the diffusion of the morphogens and the evolution of the shapes. We have developed a mathematical framework describing the coupling of diffusion and growth, that we named Developmental Partial Differential Equations. 
CQB Seminar: Tuesday March 28th 2017 12:00 pm: Anirvan Sengupta
The Rutgers Center for Quantitative Biology is pleased to announce the following seminar: Speaker: Anirvan Sengupta, Rutgers When: Tuesday March 28th 2017 12:00 pm Where: Hill 260 (Busch Campus, Rutgers) Title: Biologically Plausible Neural Networks for ICA Abstract: Independent Component Analysis (ICA) is a powerful and popular signal processing method that is used for blind source separation. As the brain clearly solves blind source separation problems, con structing a biologically plausible ICA algorithm is an important challenge. Here, we develop such an ICA algorithm which can be implemented by a neural network that satisfies the following biological constraints. The algorithm operates in the online (or streaming) setting where data samples are streamed to the algorithm sequentially, one at a time, and the algorithm computes the sources on the fly without storing any significant fraction of inputs or output in memory. The synaptic weight updates are local i.e. they depend on the activities of only the two neurons the synapse connects. Finally, unlike many other ICA algorithms, our algorithm does not require prewhitening of the inputs, which is difficult to achieve in an online setting with possibly nonstationary inputs commonplace in biology 
CQB Seminar: Tuesday March 21st 2017 12:00 pm
The Rutgers Center for Quantitative Biology is pleased to announce the following seminar: Speaker: Diego U. Ferreiro, Univ Buenos Aires When: Tuesday March 21st 2017 12:00 pm Where: Hill 260 (Busch Campus, Rutgers) Title: Frustration and the energy landscapes of repeatproteins Abstract: Natural protein molecules fold, move and function according to the information encoded in their energy landscapes. For most architectures, this information is still difficult to deconvolute from the linear sequence of amino acids, as the energy contributions are small, numerous and distant. In contrast, repeatproteins encode similar structural features in a quasilinear way, facilitating the description, evaluation and evolution of their energy landscapes. I will present and discuss the application of statistical analysis of structural and genomic data to extract physically meaningful information about repeatproteins' physiology. 
CQB Seminar: Tuesday March 7th, 2017 12:00pm: Karim Azer, Sanofi

CQB Seminar: Tuesday February 28th, 2017 12:00pm: Allen Tannenbaum, SUNY Stony Brook
The Rutgers Center for Quantitative Biology is pleased to announce the following seminar: Speaker: Allen Tannenbaum, SUNY Stony Brook When: Tuesday February 28th, 2017 12:00pm Where: Hill 260 (Busch Campus, Rutgers) Title: On the Robustness of Cancer Networks: A Geometric Approach Abstract: Cellular interactions can be modeled as complex dynamical systems represented by weighted graphs. The functionality of such networks, including measures of robustness, reliability, performance, and efficiency, are intrinsically tied to the topology and geometry of the underlying graph. Utilizing recently proposed geometric notions of curvature on weighted graphs, we investigate the features of gene coexpression networks derived from largescale genomic studies of cancer. We find that the curvature of these networks reliably distinguishes between cancer and normal samples, with cancer networks exhibiting higher curvature than their normal counterparts. We establish a quantitative relationship between our findings and prior investigations of network entropy. Furthermore, we demonstrate how our approach yields additional, nontrivial pairwise (i.e. genegene) interactions which may be disrupted in cancer samples. The mathematical formulation of our approach yields an exact solution to calculating pairwise changes in curvature which was computationally infeasible using prior methods. As such, our findings lay the foundation for an analytical approach to studying complex biological networks. 
CQB Seminar: Tuesday February 21st, 2017 12:00pm: Victor M. Preciado, U of Pennsylvania

CQB Seminar: Tuesday February 14th, 2017 12:00pm: Sahand Jamal Rahi

CQB Seminar: Tuesday February 7th, 2017 12:00pm: Cengiz Pehlevan
