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RECoVERY: New open-source software developed for analyzing SARS-CoV-2 genomes

RECoVERY: New open-source software developed for analyzing SARS-CoV-2 genomes
A team of researchers from the Istituto Superiore di Sanita (ISS), Italy, report an open-source platform-independent tool for building severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from raw sequencing reads. The tool can be used without any extra hardware or software and be run using any browser from a desktop or mobile.
SARS-CoV-2, the causative pathogen of coronavirus disease 2019 (COVID-19) has rapidly spread across the globe resulting in more than two million deaths. Next-generation sequencing technologies (NGS) have allowed complete genome sequencing of the different virus strains, providing estimations of how the virus spreads over time and geographies. ....

Lakshmi Supriya , Phd Jan , Istituto Superiore , Ion Torrent , Genome Detective Virus , Coronavirus Disease Covid 19 , Sars Cov 2 , Corona Virus , Severe Acute Respiratory , Severe Acute Respiratory Syndrome , லட்சுமி சுப்ரியா , ஃப்ட் ஜான் , அயன் நீரோடை , மரபணு துப்பறியும் வைரஸ் , உயிர் தகவலியல் , கொரோனா வைரஸ் , கடுமையானது எடுப்போசை சுவாச , கடுமையானது எடுப்போசை சுவாச நோய்க்குறி ,

Champions Oncology, Inc.: Champions Oncology Announces Partnership with Code Ocean to Expand the Functionality of Lumin Bioinformatics

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HACKENSACK, NJ / ACCESSWIRE / January 19, 2021 / Champions Oncology, Inc. (NASDAQ:CSBR), a leading global oncology technology company that is transforming drug discovery and development through data-driven research strategies, announced today a partnership with Code Ocean to expand the functionality of its SaaS program, Lumin Bioinformatics. The partnership between Champions and Code Ocean will focus on enhancements involved in data integration and sharing workflows within the Lumin platform. Users will now be equipped with a robust methodology for centralizing, storing, and organizing large amounts of their own code and data within Lumin, while leveraging single tenant hosting. Users will have the ability to upload this information directly or utilize Champions computational services to assist with integration. This new functionality establishes an entire new use case for Lumin and facilitates a customized experience for our clients. Importantly, users will now have a me ....

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Appreciating a flower's texture, color, and shape leads to better drone landings

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IMAGE: Optical flow field (blue arrows) when the drone flies straight forward. In the flight direction, the flow is smallest, making the tree in the drone s path the hardest one to.
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Credit: MAVLab/ TU Delft
If you ever saw a honeybee hopping elegantly from flower to flower or avoiding you as you passed by, you may have wondered how such a tiny insect has such perfect navigation skills. These flying insects skills are partially explained by the concept of optical flow: they perceive the speed with which objects move through their field of view. Robotics researchers have tried to mimic these strategies on flying robots, but with limited success. A team of TU Delft and the Westphalian University of Applied Sciences researchers therefore present an optical flow-based learning process that allows robots to estimate distances through the visual appearance (shape, color, texture) of the objects in view. This artificial intelligence (AI)-based ....

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New COVID-19 model shows little benefit in vaccinating high-risk individuals first

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BROOKLYN, New York, Tuesday, January 19, 2021 - The World Health Organization reports that as of January 19, 2021, there are approximately 94 million cases of COVID-19 globally, with over 2 million deaths. In the face of these numbers driven in part by an aggressive resurgence of the virus in the U.S. health authorities face a tenuous balancing act: how to enact policies to keep citizens safe while doing the least possible damage to quality of life and local economies, especially in smaller cities and towns, where short supply of intensive care units and tight budgets make the thin line between precautionary measures and normalcy even thinner. ....

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New computational tool reliably differentiates between cancer and normal cells from single-cell RNA-sequencing data

Credit: MD Anderson Cancer Center
HOUSTON In an effort to address a major challenge when analyzing large single-cell RNA-sequencing datasets, researchers from The University of Texas MD Anderson Cancer Center have developed a new computational technique to accurately differentiate between data from cancer cells and the variety of normal cells found within tumor samples. The work was published today in
Nature Biotechnology.
The new tool, dubbed CopyKAT (copy number karyotyping of aneuploid tumors), allows researchers to more easily examine the complex data obtained from large single-cell RNA-sequencing experiments, which deliver gene expression data from many thousands of individual cells.
CopyKAT uses that gene expression data to look for aneuploidy, or the presence of abnormal chromosome numbers, which is common in most cancers, said study senior author Nicholas Navin, Ph.D., associate professor of Genetics and Bioinformatics & Computational Biology. The tool ....

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