Center for Bio-Image Informatics

Engineering, Biology and Computer Science, working together.

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Seminars

Nov 29 2010: Dr. Mark Ellisman

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MULTISCALE CHALLENGES IN BRAIN SCIENCES: Bridging Gaps in Knowledge and Understanding

3PM, Nov 29, Monday in Engineering Science Building (ESB) 1001.


A grand goal in neuroscience research is to understand how the interplay of structural, chemical and electrical signals in and between cells of nervous tissue gives rise to behavior. We are rapidly approaching this horizon as neuroscientists make use of an increasingly powerful arsenal of tools and technologies for obtaining data, from the level of molecules to nervous systems. The need for a scalable and available knowledge environment and frameworks or systems to link knowledge have captured the attention of many who now work at the hybrid interface of neuroscience and information sciences - sometimes called "neuroinformatics". This talk will highlight some of the tools and data available today, illustrating what tomorrow's neuroscientists might expect from neuroinformatics in an era in which scientific discoveries will hinge increasingly on the development and use of telecommunications and information technology. A consolidated strategy for integrating neuroscience data has been to provide a multi-scale structural or spatial scaffold on which existing and accruing elements of neuroscience knowledge can be located and relationships explored from any network-linked computer. However, even data taken at similar scales from different sites, like structural and functional MRI data, are difficult to merge in the absence of agreed upon standards that would allow such non-invasive brain imaging data to be brought together. Similarly, efforts to integrate multi-scale data from different methods using a common spatial framework are hampered by incomplete descriptions of the microscopic or molecular anatomy of nervous systems. While some spatial and temporal scales are well studied and described, there are many domains where current methods have provided only sparse descriptions. Progress toward overcoming these obstacles, including approaches to bring spatial frameworks with emerging representations of knowledge in systems biology will be discussed. These and other approaches for integrating neuroscience knowledge will be highlighted using examples from activities of current projects. .

About the speaker:

Ph.D., University of Colorado, Boulder, 1976 in Molecular, Cellular and Developmental Biology. In addition to being a Founding Fellow of the American Institute of Biomedical Engineering, Dr. Ellisman has received numerous awards including a Jacob Javits award from the National Institutes of Health (NIH) and the Creativity Award from the National Science Foundation. His UCSD teaching and lecturing awards include the Department of Neurosciences Award for Outstanding Teaching in 1987 and 1992, and he was selected by UCSD as the University Lecturer in BioMedicine in 2001. He also served as the interdisciplinary coordinator for the NSF-supported National Partnership for Advanced Computing Infrastructure (NPACI) and led the Neuroscience activities for NPACI and the San Diego Supercomputer Center (SDSC) promoting biomedical research and emerging cyber infrastructure.

For further details

PDF: Ellisman.pdf

 

2009-03-16: Prof. Inigo Novales

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Current research in Retinal Studies

12 Noon, CS Conference Room (Harold Frank Hall, Room 1132).

To be decided

 

2009-03-09: John Dowling

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Organization of the Vertebrate Retina (Part 2)

12 Noon, CS Conference Room (Harold Frank Hall, Room 1132).


Professor Dowling will giving  a general overview of the vertebrate retina, focusing especially on its functional organization.  This is intended to be an informal presentation so that the audience can ask questions, raise issues, and participate in the discussions.

About the speaker:

Dr. John E. Dowling received his  Ph.D. degree in  Biology from Harvard University in 1961. He is presently Llura & Gordon Gund Professor of Neuroscience at Harvard, and Professor of  Ophthalmology (Neuroscience), Harvard Medical School.

Early in his career, Dowling worked as a researcher under Nobel Prize  winner George Wald. During this time, Dowling mapped the exchange of  retinoids between the retinal photoreceptors where they are used in  photoreception and the pigment epithelial cell where the retinoids are  stored. Because of Dowling's work, this process is now described in 
all biology textbooks. In addition, Dowling's groundbreaking work on  the functional organization of the retina laid the foundation for  understanding how the retina begins to integrate and analyze visual  information. Dowling has received numerous awards including the  Friedenwald Medal, the highest scientific award from the Association  for Research in Vision and Ophthalmology. He is an elected member of  the National Academy of Science.

Dr. Dowling has published many books, including  the classic "The  Retina: An Approachable Part of the Brain,"  Harvard University Press,  Cambridge, MA (1987);  "Neurons and Networks: An Introduction to  Neuroscience, " Harvard University Press, Cambridge, MA (1992); and   "Creating Mind: How the Brain Works,"  W. W. Norton & Co., New York,  NY (1998).

Presentation slides from John Dowling for "Organization of the Vertebrate Retina"

PDF: Dowling_Retina.pdf

PPT: Dowling_Retina.ppt

 

2009-03-02: John Dowling

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Organization of the Vertebrate Retina

12 Noon, CS Conference Room (Harold Frank Hall, Room 1132).


Professor Dowling will giving  a general overview of the vertebrate retina, focusing especially on its functional organization.  This is intended to be an informal presentation so that the audience can ask questions, raise issues, and participate in the discussions.

About the speaker:

Dr. John E. Dowling received his  Ph.D. degree in  Biology from Harvard University in 1961. He is presently Llura & Gordon Gund Professor of Neuroscience at Harvard, and Professor of  Ophthalmology (Neuroscience), Harvard Medical School.

Early in his career, Dowling worked as a researcher under Nobel Prize  winner George Wald. During this time, Dowling mapped the exchange of  retinoids between the retinal photoreceptors where they are used in  photoreception and the pigment epithelial cell where the retinoids are  stored. Because of Dowling's work, this process is now described in 
all biology textbooks. In addition, Dowling's groundbreaking work on  the functional organization of the retina laid the foundation for  understanding how the retina begins to integrate and analyze visual  information. Dowling has received numerous awards including the  Friedenwald Medal, the highest scientific award from the Association  for Research in Vision and Ophthalmology. He is an elected member of  the National Academy of Science.

Dr. Dowling has published many books, including  the classic "The  Retina: An Approachable Part of the Brain,"  Harvard University Press,  Cambridge, MA (1987);  "Neurons and Networks: An Introduction to  Neuroscience, " Harvard University Press, Cambridge, MA (1992); and   "Creating Mind: How the Brain Works,"  W. W. Norton & Co., New York,  NY (1998).

Presentation slides from John Dowling for "Organization of the Vertebrate Retina"

PDF: Dowling_Retina.pdf

PPT: Dowling_Retina.ppt

 

2007-07-23 Prof. Benjamin Reese

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Determinants of Dendritic Morphology, Connectivity, Spacing and Functional Coverage of Retinal Nerve Cells

Prof. Benjamin Reese

July 23, 2007

Abstract:

 

My lab has been exploring the determinants of dendritic morphology, connectivity and intercellular spacing that underlie the functional coverage of retinal nerve cell mosaics.Recent studies have focused on the horizontal cells of the retina, being inhibitory interneurons with dendritic fields that overlap one another, contacting the pedicles of cone photoreceptors.Because of their regular spacing, their dendrites provide a uniform coverage of the retinal surface.The developmental mechanisms establishing their intercellular spacing and morphological properties are undefined, but fate-determination events and cell-intrinsic instructions have been suggested to underlie these features. I will consider an alternative hypothesis, that interactions with neighboring cells drive the intercellular spacing and dendritic differentiation of these cells. Using a variety of natural and genetically-modified strains of mice, we have modulated the relationship between horizontal and cone cell number to study the role of homotypic and afferent density upon mosaic patterning and differentiation. A number of spatial statistics for analyzing the patterning of retinal mosaics in 2D will be discussed. Variation in horizontal cell density is shown to produce a corresponding change in the average spacing between horizontal cells and in the size of the dendritic field, while altering cone density leaves dendritic field size unaffected and does not perturb mosaic patterning, but drives higher order dendritic branching and terminal clustering. Afferent and homotypic interactions therefore generate the network properties of horizontal cells that underlie their functional coverage. Such issues have not been addressed within networks of nerve cells within the brain for a variety of reasons, partly because determining such spatial statistics in 3D is computationally demanding, and because of the difficulty in visualizing nerve cell patterning in 3D. At the end of the talk, I will describe the creation of new software tools permitting the analysis and modeling of such nerve cell patterning in three dimensions.

 

2007-04-18 Dr. David Rimm

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Imaging Solutions for Problems in Anatomic Pathology

Dr. David Rimm

Department of Pathology at the Yale University School of Medicine

April 18th, 2007

Abstract:

Professor Rimm will talk about using spectral imaging and fluorescence-based automated quantitative analysis to address current medical problems in anatomic pathology. The problems addressed will be the problem of atypical cells and pre-malignancy in cytopathology and the problem of accurate protein measurement as a mechanism to predict response to targeted therapies or to predict metastasis in breast cancer and melanoma.

 

2007-03-12 Prof James S. Duncan

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Model-Based Biomedical Image Analysis

Prof James S. Duncan

Biomedical Engineering, Diagnostic Radiology and Electrical Engineering, Yale University

Mar. 12, 2007

Abstract:

 

The development of methods to accurately and reproducibly recover useful quantitative information from medical images is often hampered by uncertainties in handling the data related to: image acquisition parameters, the variability of normal human anatomy and physiology, the presence of disease or other abnormal conditions, and a variety of other factors. This talk will review image analysis strategies that make use of models based on geometrical and physical/biomechanical information to help constrain the range of possible solutions in the presence of such uncertainty. The discussion will be focused by looking primarily at several problem areas in the realms of neuroanatomical structure analysis and cardiac function analysis, with an emphasis on image segmentation and motion/deformation tracking. The presentation will include a description of the problem areas and visual examples of the image datasets being used, an overview of the mathematical techniques involved and a presentation of results obtained when analyzing actual patient image data using these methods. Emphasis will be placed on how image-derived information and appropriate modeling can be used together to address the image analysis and processing problems noted above.
 

2006-11-09 Christoph Best

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Challenges for Intelligent Image Processing in Cryo-Electron Microscopy

Christoph Best

Dept. of Molecular Structural Biology, Max Planck Institut fuer Biochemie, Martinsried, Germany

Nov 9, 2006

Abstract:

Cryo-electron microscopy enable the imaging of macromolecular complexes and cellular structures in a near-natural state at molecular resolution. Recent developments in preparation, instrumentation, and automation carry the promise of imaging molecular structures at sub-nanometer resolutions in their native environment, as well as creating molecular maps of the macromolecular complexes in the living cell. These advancements pose unique new informatics problems in image processing. In particular, methods from machine learning and probabilistic modeling will play a large role in classifying images, combining them into three-dimensional structures, and extracting information from them. I will discuss several examples where modern informatics methods may improve electron microscopy such as model-free maximum-likelihood classification of projection images, particle picking through support vector machines, and 3D reconstruction from random projections using the Baum-Welch algorithm and Level Set methods.

 

2006-01-26 Prof. Badri Roysam

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Multi-dimensional Image Analysis Methods for Modern Optical Microscopy

Professor Badri Roysam

ECSE Department, Rensselaer Polytechnic Institute

Jan 26, 2006

Abstract:


Modern optical microscopes, aided by a family of support technologies, have matured into a truly multi-dimensional imaging tool for conducting diverse biological investigations at the sub- cellular, cellular, and tissue levels. The widespread availability of confocal and multi-photon microscopes and high-NA objectives, have made high-resolution (axial and lateral) three-dimensional (3-D) imaging of multiple structures and functional markers routine. From a systems biology perspective, modern microscopy is valuable for its ability to record processes in the spatial context of intact tissue, unlike biochemical assays, gene arrays and flow cytometry, in which spatial information is unavoidably disrupted. A variety of complementary advances in biochemistry (e.g., conjugated quantum dots, fluorescent proteins), image pre-processing software, and high- throughput specimen preparation serve to magnify the capabilities of optical microscopy.

There is a compelling need for technologies to translate this wealth of imaging data into quantitative insight. Specifically, two types of needs exist: (i) analysis of complex data sets involving interactions among multiple structures and functional markers, and multiple imaging dimensions; and (ii) analysis of large batches of such images. Quantitative measurements are needed in contexts ranging from hypothesis testing, drug discovery, assay development, high- throughput assays, quantitative tissue engineering, cytomic mapping.

In this talk, Dr. Roysam will describe the FARSIGHT project at Rensselaer that is producing software technologies that address the above needs in a systematic manner. This project is specifically designed for the multi-dimensional imaging capabilities of modern optical microscopy, and the complex image analysis needs of contemporary cell/tissue biology.

 

2004-11-12 Arun Majumdar

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Micro and Nanostructured Materials and Devices for Biomolecular Analysis

 

Arun Majumdar

Department of Mechanical Engineering, University of California, Berkeley

Nov. 12, 2004

Abstract:

Over the last decade, we have witnessed an exponential growth in genomic information, which was highlighted by the Human Genome Project.Accompanying that was an exponential decrease in cost per sequenced gene. While these trends are expected to continue in genomics, they also provoke the question of whether there would be similar increases in information for other biomolecules, such as proteins, which are more complex in their structure and function. As part of this talk, I will present some of our and others’ work in developing technologies that could lead to rapid biomolecular analysis. In particular, I will focus on analysis based on cantilever mechanics, electrical capacitance, nanofluidics, and nanoparticle imaging. One of the goals of this talk is to catalyze discussion on how such technologies could address important biological questions that are difficult to address otherwise.

 


Weekly Meeting

These are the details for the meeting of this week.

DATE:  Wed. April 30th
TIME 11.45 a.m.
LOCATION: Eng I room 4164

Luca will give research updates.