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[Colloquium] Computational Aspects of Single Particle Tracking in Fluorescence Microscopy

April 29, 2015

Watch Colloquium: 


  • Date: Thursday, 4/30/15
  • Time: 11:00 AM - 12:15 PM
  • Place: Mechanical Engineering, Room 218

Speaker: Mark Olah, postdoctoral fellow, UNM

Title: Computational Aspects of Single Particle Tracking in Fluorescence Microscopy

Abstract: In fluorescence microscopy, individual molecules can be labeled by fluorescent tags and their motion and interactions can be captured as a video sequence. Fundamental limits on optical systems restrict the resolution of the images of these fluorescent probes to approximately 250nm. However, recent advances in machine-learning-based methods have allowed the individual fluorescent molecule positions to be estimated to much higher precision (<10nm) by using probabilistic models and Monte Carlo techniques. With this increase in precision it is now
possible to extract individual molecular trajectories from captured video sequences. This talk will cover the computational aspects of the various algorithms and techniques used in single particle tracking. In particular, we will discuss the computational challenges associated with analyzing data from a new type of hyper-spectral microscope developed in the Physics department at UNM. This microscope captures sequences of images in 128 different colors simultaneously, hence each frame of a video is 3D where the dimensions are X, Y and Lambda(wavelength). This
added dimensionality allows for more sophisticated experiments, but also poses computational and conceptual challenges that must be addressed with techniques from several different areas of computer science including 3D visualization, Markov Chain Monte Carlo estimation, machine learning, numerical optimization, image processing, and combinatorial optimization.

Bio: Dr. Mark Olah is currently a postdoctoral researcher at UNM, working on machine learning and Bayesian inference problems that arise in the analysis of single-molecule fluorescence microscopy data. Dr. Olah is being co-advised by Prof. Keith Lidke in the Physics Department and Prof. Diane Lidke in the Pathology Department. Dr. Olah received BS degrees in both computer science and mathematics from Carnegie Mellon
University in 2004. In 2012, Dr. Olah received his Ph.D. from the UNM Department of Computer Science, under the advisement of Prof. Darko Stefanovic, where he worked on Monte Carlo simulations of single molecule motion in the context of nanoscale robotics.