Using a Topological Descriptor to Investigate Structures of Virus Particles.

March 23rd, 2014

The Digital Imaging and Graphics (DIG) Group in the CUNY PhD Program In Computer Science is holding a seminar jointly with the New York Topology Seminar on Friday, April 11, from 3:30 pm to 5:30 pm in the Computer Science Thesis Room (Room 4421 at the Graduate Center).

3:30 – 4:00: Tea and informal discussions.

4:00 – 5:00: Presentation by Lucas Oliviera, PhD Program in Computer Science


Title: Using a Topological Descriptor to Investigate Structures of Virus Particles.
Abstract: An understanding of the three-dimensional structure of a biological macromolecular complex is essential to fully understand its function. A component tree is a topological and geometric image descriptor that captures information regarding the structure of an image based on the connected components determined by different grayness thresholds. We believe interactive visual exploration of component trees of (the density maps of) macromolecular complexes can yield much information about their structure. To illustrate how component trees can convey important structural information, we consider component trees of four recombinant mutants of the procapsid of a bacteriophage (cystovirus phi6), and show how differences between the component trees reflect the fact that each non-wild-type mutant of the procapsid has an incomplete set of constituent proteins.

5:00 – 5:30: Questions and informal discussions.

Computational Methods for Three-Dimensional Microscopy Reconstruction (Forthcoming Book Chapter)

January 6th, 2014

Approaches to the recovery of three-dimensional information on a biological object, which are often formulated or implemented initially in an intuitive way, are concisely described here based on physical models of the object and the image-formation process. Both three-dimensional electron microscopy and X-ray tomography can be captured in the same mathematical framework, leading to closely-related computational approaches, but the methodologies differ in detail and hence pose different challenges. The editors of this volume, Gabor T. Herman and Joachim Frank, are experts in the respective methodologies and present research at the forefront of biological imaging and structural biology.

Together with my co-authors Gabor T. Herman and T. Yung Kong, we have chapter titled “Using Component Trees to Explore Biological Structures” inpress in this book. The abstract is reproduced bellow:

“An understanding of the three-dimensional structure of a macromolecular complex is essential to fully understand its function. This chapter introduces the reader to the concept of a component tree, which is a compact representation of the structural properties of a multidimensional image (such as a molecular density map of a biological specimen), and then presents ongoing research on the use of such component trees in interactive tools for exploring biological structures. Com- ponent trees capture essential structural information about a biological specimen, irrespective of the process that was used to obtain an image of the specimen and the resolution of that image. We present various scenarios in which component trees can help in the exploration of the structure of a macromolecular complex. In addition, we discuss ideas for a docking methodology that uses component trees.”

 

IEEE Signal Processing in Medicine and Biology Symposium (SPMB13)

October 14th, 2013

Saturday, December 7, 2013 Polytechnic Institute of New York University spectrogram Signal processing plays a broad role in the development of medical devices and in the analysis of physiological signals. This public symposium provides a forum for the presentation of research and development in signal processing (broadly defined, i.e. including image processing, 3D reconstruction, etc.) in medicine and biology.

The symposium is sponsored by IEEE-USA, the Polytechnic Institute of New York University (NYU-Poly) and the City College of New York (CCNY). The technical co-sponsored is the IEEE Engineering in Medicine & Biology Society. We invite engineers, scientists, practitioners, and students to submit papers or abstracts for presentation at the symposium, or to attend the symposium. Prospective presenters may submit either (1) an original manuscript for peer review to be considered for publication in IEEE Xplore, or (2) an abstract, to be presented at the symposium, that may describe preliminary results, etc. The technical program will be posted on this site before the symposium. The symposium will be held on the NYU-Poly campus in downtown Brooklyn.

more information: http://eeweb.poly.edu/SPMB/

Xmipp Workshop

May 17th, 2013

The Workshop covers the details of the Xmipp software package, that is used for reconstructing 3D maps from sets of individual particle images. The majority of the workshop consists of hands-on sessions designed to familiarize the attendees with the public-domain Xmipp software.

 

This Workshop is sponsored by the Ph.D. Program in Computer Science of The City University of New York.

Location: The Graduate Center, City University of New York (Room 6495, The Graduate Center, CUNY, 365 Fifth Avenue, New York, NY 10016, USA).

Date: July 31st, 1:30-5:30 pm.

 

more information here

 

Minisymposium on Computational Methods for Three-Dimensional Microscopy Reconstruction

May 17th, 2013

See more information here: http://franklab.cpmc.columbia.edu/franklab/minisymposium

Provably Robust Simplification of Component Trees of Multidimensional Images (book chapter)

June 27th, 2012

Book CoverAbstract We are interested in translating n-dimensional arrays of real numbers (images) into simpler structures that nevertheless capture the topological/geometrical essence of the objects in the images. In the case n = 3 these structures may be used as descriptors of images in macromolecular databases. A foreground component tree structure (FCTS) contains all the information on the relationships between connected components when the image is thresholded at various levels. But unsimplified FCTSs are too sensitive to errors in the image to be good descriptors. This chapter presents a method of simplifying FCTSs which can be proved to be robust in the sense of producing essentially the same simplifications
in the presence of small perturbations. We demonstrate the potential applicability of our methodology to macromolecular databases by showing that the simplified FCTSs can be used to distinguish between two slightly different versions of an adenovirus.

Tree representation of digital picture embeddings

June 27th, 2012

Paper in Journal of Visual Communication and Image Representation

Abstract: It is often the case that the same object is imaged in different ways, resulting in digital pictures of (some parts of) it at different resolutions. This leads to the combinatorial problem of “embedding” one of these pictures into the other in a way that corresponds to physical truth. In this paper we present a mathematical formulation of this intuitive concept of embedding. We also show, using a tree representation of digital pictures, how picture embedding relates to tree embedding, which has been a subject of much study in combinatorial computer science (mostly for reasons other than application to digital pictures). [see more]

Announcement:

March 31st, 2012

Minisymposium on Computational Methods for Three-Dimensional Microscopy Reconstruction.
For details, see
http://www.dig.cs.gc.cuny.edu/workshops/Mini_Symposium_2012.html

Organized by Gabor T. Herman of CUNY and Joachim Frank of Columbia University.
Location: The Graduate Center of the City University of New York.
Date: June 15, 2012.

Spring 2010 -Graduated Center course: Multidimensional Data Structures

October 29th, 2010

This course is based on those sections of the highly acclaimed book Foundations of Multidimensional and Metric Data Structures with which the professor teaching the course has practical experience. These sections are the ones relevant to computer graphics, databases, image processing, pattern recognition, and solid modeling.

Minisymposium on Computational Methods for Three-Dimensional Microscopy Reconstruction

October 29th, 2010

Minisymposium on Computational Methods for Three-Dimensional Microscopy Reconstruction
Room 4102, Graduate Center of the City University of New York
November 8, 2010

More information here [PDF]