Researchers at the Georgia Institute of Technology have developed a computer program that trains itself to predict genes in the DNA sequences of fungi. Understanding the recently sequenced fungal genomes can help in developing and producing critical pharmaceuticals. Gene prediction can also help to identify potential targets for therapeutic intervention and vaccination against pathogenic fungi.

Mark Borodovsky, director of Georgia Tech’s Center for Bioinformatics and Computational Genomics, and his colleagues expanded the eukaryotic genome self-training software program they developed in 2005 to address the issue that fungal genes are more complex than other eukaryotes. Unlike other programs that require a pre-determined training set along with the genome sequence, GeneMark.hmm-ES (BP) only requires the genome sequence. The program is able to iteratively identify the correct algorithm parameters from the anonymous sequence.

“The enhanced program predicted fungal genes with higher accuracy than either the original self-training algorithm or known algorithms with supervised training,” noted Borodovsky. “And because we didn’t need any additional training information for our program, the sequencing teams could immediately proceed with gene annotation right after the genomic sequence was in hand, without spending time and effort to extract a set of validated genes necessary for estimating parameters of traditional algorithms.”

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The sixth annual National Nanoengineering Conference returns to Boston this year on November 12-13 at the Boston Colonnade Hotel, featuring the fourth annual Nano 50 Awards, recognizing top 50 technologies, innovators, and products that have significantly impacted the development of nanotechnology.

This year’s presentation at the awards dinner will be “Nano Science & Technology for National Security”, presented by Dr. Cherry Murray, Principal Associate Director for Science and Technology, Lawrence Livermore National Laboratory. Dr. Murray became the Principal Associate Director for Science and Technology (PAD-S&T) at Lawrence Livermore National Laboratory on October 1, 2007, after joining the Lab in December, 2004 as Deputy Director for Science and Technology. Murray is a physicist who has been nationally recognized for her work in surface physics, light scattering, and complex fluids. She is a member of the National Academy of Sciences, the National Academy of Engineering, and a Fellow of the American Academy of Arts and Sciences. Discover Magazine named her one of the “50 Most Important Women in Science” in 2002.

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Scientists from Novartis Institute for Biomedical Research and the British Columbia Cancer Agency have demonstrated a new instrument that makes it possible to detect and quantify multiple different clinically important proteins in a single tumor sample using conventional staining. Currently, pathologists usually need a separate tissue slice for each protein they want to examine, making it impossible to see how molecules interact within individual cells.

The instrument uses a CRi Nuance(TM) multispectral imaging camera, which captures information from multiple wavelengths in the visible and infrared, an automated microscope, and novel machine learning-based software to extract data from images. The analysis shows which proteins are being expressed and the expression level. Up to 180 tumors from different patients can be analyzed in an hour by a computer using this process. The technology is designed to be used by pathologists to reveal new data that can help researchers develop targeted therapies.

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Researchers at the University of North Carolina at Chapel Hill School of Medicine have transformed cells from human skin into cells that produce insulin, the hormone used to treat diabetes. The breakthrough may one day lead to new treatments for the millions of people affected by the disease, researchers say.

The approach involves reprogramming skin cells into pluripotent stem cells, or cells that can give rise to any other fetal or adult cell type, and then inducing them to differentiate, or transform, into cells that perform a particular function – in this case, secreting insulin. Several recent studies have shown that cells can be returned to pluripotent state using “defined factors” – specific proteins that control which genes are active in a cell – a technique pioneered by Dr. Shinya Yamanaka, a professor at Kyoto University in Japan.

“Not only have we shown that we can reprogram skin cells, but we have also demonstrated that these reprogrammed cells can be differentiated into insulin-producing cells which hold great therapeutic potential for diabetes,” said Yi Zhang, Ph.D., the study’s lead author and professor of biochemistry and biophysics at UNC.

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A Bluetooth system developed at the University of Michigan tells blind or sighted pedestrians about points of interest along their path as they pass them. Called Talking Points, the system is the first known to use Bluetooth, allowing people to operate it entirely with voice commands, and incorporate community-generated content through a website.

The system uses a mobile device to pick up the Bluetooth signals and speak or display information to the user. Bluetooth beacons, or tags, would be located at points of interest where owners wish to give information to Talking Points users. A website would allow beacon owners to program their tags. Once a beacon is added, other community members could add their comments about the point of interest.

“Talking Points can be viewed as a first step in the direction of an audio virtual reality designed for people with blindness and very useful to the sighted community as well,” said James Knox, adaptive technology coordinator for the University’s Information Technology Central Services and one of the system’s developers.

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