Current year seminars

NOTE: this page is written and maintained by Eduardo Sontag (eduardo.sontag@gmail.com)


CQB Seminar: Tuesday April 25th 2017 12:00 pm, Chang Chan, Cancer risk prediction in mice and humans with germline p53 mutations

posted Apr 23, 2017, 6:39 PM by eduardo sontag

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

posted Apr 23, 2017, 6:38 PM by eduardo sontag

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 re-alignment of circadian rhythms.

CQB Seminar: Tuesday April 11th 2017 12:00 pm, Nastassia Pouradier Duteil

posted Apr 23, 2017, 6:37 PM by eduardo sontag

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.

We applied our framework to the specific case of the activation of the epidermal growth factor receptor (EGFR) pathway, a highly-conserved signaling pathway across animals, that controls both the posterior-anterior and the dorsal-ventral axes during Drosophila melanogaster oogenesis. The TGF-alpha-like ligand Gurken (GRK) is secreted from around the oocyte nucleus to the perivitelline space and activates EGFR in the overlaying follicle cells. Complexity is found in the dynamic localization of the oocyte nucleus, and hence the source of GRK. Early, the nucleus is present at the posterior end. Later, the nucleus is situated at the dorsal anterior side of the oocyte. Thus, EGFR activation is dynamic. Furthermore, the oocyte within the egg chamber continuously grows during oogenesis. Lastly, the overlaying follicle cells gradually shift from anterior to posterior. Current models consider solely GRK diffusion from a static location, and in an unchanging egg chamber. Based on experimental data, we built a mathematical model using reaction-diffusion PDEs to recapitulate the spatiotemporal dynamic activation of EGFR, including the evolution of the egg chamber and the shift of the overlaying cells. Our model reveals the crucial role of growth and cell movement in shaping the distributions of GRK and signaling.

CQB Seminar: Tuesday March 28th 2017 12:00 pm: Anirvan Sengupta

posted Mar 25, 2017, 7:14 AM by eduardo sontag

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 pre-whitening of the inputs, which is difficult to achieve in an online setting with possibly non-stationary inputs commonplace in biology 

CQB Seminar: Tuesday March 21st 2017 12:00 pm

posted Mar 2, 2017, 6:17 AM by eduardo sontag

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 repeat-proteins

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, repeat-proteins encode similar structural features in a quasi-linear 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 repeat-proteins' physiology.

CQB Seminar: Tuesday March 7th, 2017 12:00pm: Karim Azer, Sanofi

posted Feb 22, 2017, 10:12 AM by eduardo sontag   [ updated Mar 2, 2017, 6:19 AM ]

The Rutgers Center for Quantitative Biology is pleased to announce the following seminar: 

SpeakerKarim Azer, Sanofi

When: Tuesday March 7th, 2017 12:00pm

Where: Hill 260 (Busch Campus, Rutgers)

Title: Mathematical biology and pharmacology models in Pharma: challenges and applications

Abstract: Mathematical biology and pharmacology models are increasingly utilized in the pharmaceutical industry, recognizing the need for improving the probability of success or reducing the cost of drug development. More mechanistic, quantitative systems pharmacology (QSP) models are being leveraged to aid in the identification of novel targets in early research, in the translational medicine activities for bringing molecules into the clinic, and for achieving proof of mechanism, and understanding variability in response to novel compounds in later clinical development.

In this talk, we provide an overview on the development and application of QSP models in pharma. Several applications will be presented highlighting the impact these models are having. We will close with a discussion of the mathematical and computational challenges facing this field and highlight opportunities for research.






CQB Seminar: Tuesday February 28th, 2017 12:00pm: Allen Tannenbaum, SUNY Stony Brook

posted Feb 20, 2017, 7:07 AM by eduardo sontag

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 co-expression networks derived from large-scale 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, non-trivial pair-wise (i.e. gene-gene) interactions which may be disrupted in cancer samples. The mathematical formulation of our approach yields an exact solution to calculating pair-wise 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

posted Feb 11, 2017, 9:42 AM by eduardo sontag


The Rutgers Center for Quantitative Biology is pleased to announce the following seminar: 

SpeakerVictor M. Preciado, U of Pennsylvania

When: Tuesday February 21st, 2017 12:00pm

Where: Hill 260 (Busch Campus, Rutgers)

Title: Optimal Resource Allocation to Control Epidemic Outbreaks in Networked Populations

Abstract: We study the problem of controlling epidemic outbreaks in networked populations by distributing protection resources throughout the nodes of the network. We assume that two types of protection resources are available: (i) Preventive resources able to defend individuals in the population against the spreading of the disease (such as vaccines or disease-awareness campaigns), and (ii) corrective resources able to neutralize the spreading (such as antidotes). We assume that both preventive and corrective resources have an associated cost and study the problem of finding the cost-optimal distribution of resources throughout the networked population. We analyze these questions in the context of a viral outbreak and study the following two problems: (i) Given a fixed budget, find the optimal allocation of preventive and corrective resources in the network to achieve the highest level of disease containment, and (ii) when a budget is not specified, find the minimum budget required to eradicate the disease. We show that both resource allocation problems can be efficiently solved for a wide class of cost functions. We illustrate our approach by designing optimal protection strategies to contain an epidemic outbreak that propagates through the air transportation network.

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

posted Feb 7, 2017, 5:49 PM by eduardo sontag   [ updated Feb 7, 2017, 5:50 PM ]


The Rutgers Center for Quantitative Biology is pleased to announce the following seminar: 

SpeakerSahand Jamal Rahi, Rockefeller University

When: Tuesday February 14th, 2017 12:00pm

Where: Hill 260 (Busch Campus, Rutgers)

Title: Dynamics: Challenge and tool for understanding living systems

Abstract: A central challenge in biology is to predict system behavior in time, given incomplete knowledge, strong interactions, and noise. We have pursued multiple approaches to building predictive dynamical descriptions of biological systems, making progress toward general principles. We have focused on three specific problems: 1) The number of global oscillators controlling the 'cell cycle', the process by which cells replicate, had been unresolved. This left a number of fundamental questions unanswered: How do different processes sync up during the cell cycle? How can the cell cycle be arrested? We found that one central oscillator controls two major cell cycle processes, periodic phosphorylation/degradation and transcription, contradicting previous views. However, we also found exceptions to this rule; pursuing one such gene, we discovered a new, counter-intuitive genetic interaction between an inhibitor and a target, which violates the usual rules of genetics. 2) Can dynamic perturbations be used to identify molecular circuit topologies? We discovered dynamic 'response signatures' for specific circuit topologies and used them to solve previously hard-to-resolve questions: We identified the circuit responsible for timing robustness in yeast cell cycle control as well as a circuit leading to adaptation in the C. elegans olfactory sensory neuron AWA. 3) Do cell cycle checkpoints 'fail' in predictable patterns? A mathematically optimal checkpoint strategy, which we derived, predicts how cell cycle checkpoints fail as a function of the number of errors. Our preliminary experimental results agree with our predictions but challenge current views in the field; checkpoint failure may be a more common phenomenon than previously thought.




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

posted Jan 30, 2017, 9:30 AM by eduardo sontag


The Rutgers Center for Quantitative Biology is pleased to announce the following seminar: 

SpeakerCengiz Pehlevan, Simons Foundation

When: Tuesday February 7th, 2017 12:00pm

Where: Hill 260 (Busch Campus, Rutgers)

Title: Blind nonnegative source separation using biological neural networks

Abstract: Extraction of latent causes, or sources, from complex stimuli is essential for making sense of the world. Such stimuli could be mixtures of sounds, mixtures of odors, or natural images. If supervision, or ground truth, about the causes is lacking the problem is known as blind source separation. Here, we address a special and biologically relevant case of this problem when sources (but not the mixing matrix) are known to be nonnegative, for example, due to the physical nature of the sources. We search for the solution to this problem that can be implemented using biologically plausible neural networks. Specifically, we consider the online setting where the dataset is streamed to a neural network. The novelty of our approach is that we formulate blind nonnegative source separation as a similarity matching problem and derive neural networks from the similarity matching objective. Importantly, synaptic weights in our networks are updated per biologically plausible local learning rules. The resulting network architecture is reminiscent of the early stages of sensory processing in the brain.

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