Strand has developed accurate image analysis solutions for microarray images and high throughput X-ray crystallography. These are currently available with Strand for licensing. Strand has expertise to extend these to apply to other focus areas.

Chitraka DNA Microarray technology has emerged as a powerful tool for genome scale expression studies, disease gene identification, genotyping and diagnostics. DNA microarray or gene chip is a miniature device wherein complementary DNA (probes) for each of the thousands of genes is spotted or in situ synthesized on a solid support (like a small microscopic glass slide). The expression levels of corresponding genes are then measured by capturing labeled RNAs or cDNAs prepared from a particular tissue sample.

Chitraka, Image Acquisition, Analysis & Management is a product for semi-automatic recognition and quantification of expressed gene spots from microarray experiments. Image analysis software performs three fundamental processes of image analysis: gridding, segmentation and information extraction.

Key features of Chitraka:

1. Multiple Scanner Acquisitions - Import images from multiple scanners from different vendors.
2. Image Formats - Full support for 16-bit grayscale TIFF images
3. Multiple Channel Experiments - channel image analysis (Cy3 and Cy5) Imaging Operations - Quality control of images to reduce skewing/rotation. Image enhancement for contrast, brightness, sharpness, multiple zoom levels.
4. Array Lists - Support for array list files such as GAL.
5. Quantification - Automatic spot segmentation and accurate spot boundary identification. Automatic doughnut spot detection and compensation.
6. Gridding - Automatic fine tuning of level one and level two grids
7. User Interface - Grid by grid view for convenient block navigations in large multi-level array lists.
8. Data Views - Automatically generates Scatter Plots and/or Histograms of any analysis measurements

Screenshots

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Sphatika Sphatika is a crystal image classification tool for high throughput X-ray crystallography. It classifies protein crystals into two broad categories, one comprising crystal hits and harvestable crystals and the other comprising empty wells, clear drops and precipitates.

The accuracy achieved is more than 92% on harvestable crystals and crystal hits together with a 20% false positive rate. With Sphatika running on a cluster, hundreds of thousands of images can be processed in a day, and the results of classification can be directly used, with minimal human intervention.

Key Features:

1. Advanced and proprietary image processing techniques used to extract significant features
2. Accuracy north of 94% on several data sets and north of 90% on the whole
3. Scalable on industry standard hardware clusters
4. Automated two way (Crystal/Non-crystal) or four-way (Crystal/ Harvestable/ Clear/ Precipitate) classifier