Integrating image analysis algorithms in a web interface for the quantification of microtubule dynamics.

We present improvements to a web interface and an integrated computational tracking algorithm for quantitative analysis of microtubule dynamics in live-cell microscopy images. Based on a previously implemented system, more new functionalities have been added to the interface. The system also integrates a computational tracking algorithm to aid the analysis.

A Web Interface for the Quantification of Microtubule Dynamics.

We propose a web interface that allows researchers to quantify and analyze microtubule confocal images online. Most analyses of microtubule confocal images are performed manually using very simple software or tools. Analysis results are stored locally within each collaborator with different styles and formats.

Automatic tip selection for microtubule dynamics quantification.

Microtubule (MT) dynamics quantification includes modeling of elongation, rapid shortening, and pauses. It indicates the effect of the cancer treatment drug paclitaxel because the drug causes MTs to bundle, which will in turn inhibit successful mitosis of cancerous cells. Thus, automatic MT dynamics analysis has been researched intensely because it allows for faster evaluation of potential cancer treatments and better understanding of drug effects on a cell.

Automatic microtubule tracking for QD-based in vivo cell imaging and drug efficacy study.

Microtubules (MT) are dynamic polymers that rapidly transition between states of growth, shortening, and pause. These dynamic events are critical for many microtubule functions such as intracellular trafficking and signaling. In addition, cancer chemotherapy drugs that target microtubules, such as the taxanes and the vinca alkaloids, are known to suppress microtubule dynamics at low doses, leading to mitotic arrest and cell death.

Detecting and quantifying biomarkers of risk for colorectal cancer using quantum dots and novel image analysis algorithms.

Colorectal cancer, the second leading cause of cancer deaths in the United States, is a molecular disease that is largely lifestyle determined and preventable. While heart disease has been sharply declining, in large part from widespread use of biological measurements that indicate risk ("biomarkers of risk"), such as blood cholesterol, to motivate and guide preventive treatment, colorectal cancer is a disease for which mortality rates have changed little and for which there have been no biomarkers of risk. Based on new knowledge about the molecular basis of colorectal cancer we developed and validated a panel of treatable biomarkers of risk that can be measured in rectal biopsies using automated immunohistochemistry and semi-automated image analysis.

Bioconjugated quantum dots for multiplexed and quantitative immunohistochemistry.

Bioconjugated quantum dots (QDs) provide a new class of biological labels for evaluating biomolecular signatures (biomarkers) on intact cells and tissue specimens. In particular, the use of multicolor QD probes in immunohistochemistry is considered one of the most important and clinically relevant applications. At present, however, clinical applications of QD-based immunohistochemistry have achieved only limited success.

Computer assisted analysis of microtubule dynamics in living cells.

Microtubules are dynamic polymers that rapidly transition between states of growth, shortening, and pause. These dynamic events are critical for basic cellular processes, especially cell division. Typically, these events are quantified by imaging microtubule movements over time, which results in large data sets that require rigorous quantitative analysis.