Department of Mathematics
CCNY Data Science, Networks, and Biology SeminarOrganizers
Beginning this semester, the Mathematics, Biology, and Computer Science departments are jointly organizing an interdisciplinary seminar on the theme of Data Science, Networks, and Biology. The theme is intended to be interpreted broadly, and a purpose of the seminar is to stimulate synergy about these topics across the campus. We welcome further involvement broadly, at any level of interest or activity.
Please distribute to anyone who might be interested. Contact Shirshendu Chatterjee (firstname.lastname@example.org) or Mike Shub (email@example.com) with any questions, including speaker suggestions. To be added or removed to the mailing list, send an email to firstname.lastname@example.org.
Thursday, May 04, 2017, 03:30PM, NAC 4/156Prof. Marilyn Gunner (CCNY Physics), Proton pumping and electron tunneling: physical principles to power the cell
Cells store energy in a proton gradient. Protons are pumped through membrane embedded proteins from the N-side of the membrane, with fewer protons, to the more positive P-side. The energy to build the gradient comes from sunlight in photosynthesis or from energy liberated by redox chemistry such as in the reduction of oxygen in cytochrome c oxidase. The proton gradient fuels the transfer of ions and substrates across the membrane needed for cell signaling and metabolism and the production of ATP, the universal energy currency for biochemical reactions. I will describe the basic rules needed to pump protons, how electron tunneling can be used to carry out reactions to build the gradient and how in F1/FO ATPase the proton gradient is used to fuel mechanical work.
Thursday, May 18, 2017, 03:30PM, NAC 4/156Basilis Gidas (Division of Applied Mathematics, Brown University), Finding Genes and Towards a Mathematical Framework for Artificial Intelligence and Biological Systems
The first half of the lecture will be on a statistical model for finding genes in the human genome. The model contains two parts: (a) A finite network (graph) which represents the overall architecture of a gene. The vertices in the network represent DNA signals (small patterns) associated with a gene and which are recognized by proteins and enzymes involved in the transcription and translation of genes. The edges of the network correspond to interactions among these signals and represent statistical variability in the architecture across genes; (b) each signal and each part of a gene is a piece of DNA with a random length as well as a random variability of its nucleotide sequence. The second part of the model articulates these variabilities.
The above gene finding procedure is conceptually similar to what is believed to underlie speech recognition whereby recognition involves two types of information: The acoustic signal represented by a concatenation of phonemes, and global regularities articulated by grammars (or syntax). The underpinning process in visual recognition is undoubtedly similar. And so is – many practitioners believe – the functioning of biological processes whereby two principles are at work: physics (biochemistry) and evolution. Physics controls the biochemical interaction of macromolecules, but it is evolution that produced the perfect “code” or “syntactic language” for the collective behavior of genes (Gene Regulatory Networks), or the collective behavior of proteins in Signal Transduction Pathways in cell growth, cell division or immunology. While specific questions and application in speech, vision, and biology have seen impressive advances and have lead to a great deal of mathematical innovation (e.g. modern statistical learning), an underpinning mathematical framework is missing. Though we do not have the framework, we know quite a bit of some of the problems the framework needs to articulate and some of the properties it needs to have. Building on the gene finding process, the second part of the talk will aim at identifying some key sources that makes the information processing in cognition and biology difficult, and hint towards a coherent hierarchical/grammatical framework.
Most recent talks
Thursday, March 30, 2017, 03:30PM, NAC 4/156Prof. Lucas Parra (CCNY Biomedical Engineering), On Brainwaves and Videos and Video Games
What are the immediate neural response of the brain to natural stimuli, in particular audiovisual narratives and video games? To answer this question we record EEG while subjects are exposed to the identical audiovisual narratives and measure inter-subject correlation, which captures how similarly and reliably different people respond to the same natural stimulus. We find that inter-subject correlation of EEG is strongly modulated by attention, correlates with long term memory, and provides a quantitative estimate for "audience engagement". In children and adolescents watching videos we find changes with age and gender that are consistent with an increase in diversity of brain responses as they mature. During video game play, which are unique experiences that preclude correlation across subjects, we measure the strength of stimulus-response correlations instead. We found that correlation with both auditory and visual responses drive the correlation observed between subjects for video and that they are are modulated by attention in video game play. Importantly, the strongest response to visual and auditory features had nearly identical neural origin suggesting that the dominant response of the brain to natural stimuli is supramodal.
Wednesday, November 30, 2016, 03:30PM, NAC 7/219Jonathan Levitt (CCNY Biology), The spatial organization of interareal connections in mammalian visual cortex
The mammalian cerebral cortex contains a number of distinct areas that mediate visual perception. There are several dozen distinct visual areas in primates, over half of the entire cortical mantle. Neurons in each of these regions are arranged topographically; neighboring neurons respond to visual stimuli that fall on adjacent regions of the retina (i.e. different regions of visual space). However, the precise map of visual space differs in each of these areas. These visual cortical areas in the adult mammalian brain are linked by a network of interareal feedforward and feedback circuits that are broadly topographic – source and target neurons sit in largely corresponding regions of the visual field map. A major interest of my laboratory is to characterize the organization of these anatomical circuits linking different areas. I will describe studies on the topographic precision and general organization of these circuits in the adult brain, and how they refine from an immature state postnatally.
Wednesday, November 09, 2016, 03:30PM, NAC 7/219Yingli Tuan (CCNY Electrical Engineering), Computer vision technologies to assist blind persons
In this talk, I will introduce our research of applying computer vision technologies to assist visually impaired or blind persons. In particular, this talk will focus on scene text detection extraction and indoor navigation. Text information widely exists in natural scene and serves as a significant indicator for many vision-based applications. Automatic extracting text information from natural scene images is still a challenging task due to complex background outliers and variations of text patterns. We have developed a prototype navigation system in Android platform by combining computer vision and robotics SLAM technologies to assist blind users in navigating across multiple floors.