Using the SVM method to predict enhancers from tissues and cell lines

| January 14, 2019

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A team of researchers has developed a computational bioinformatic method to predict and accurately locate enhancer regions on cell lines. Gene expression is a complex process that is regulated by a set of factors. These include transcriptional regulatory elements. One type of regulatory element includes short DNA regions that help in transcription efficiency through the use of several transcription factors. These are called enhancers.

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Our team improves quality of life by being the go-to place for developing cool and intuitive self-care and remote monitoring technologies for people with chronic diseases. We attract multidisciplinary talents including engineers, software developers, designers, project managers, and researchers. Leveraging our clinical connections with healthcare organizations globally, we develop technologies from users’ perspective, and evaluate our technologies to collect real data to assess their effectiveness and foster changes to better healthcare delivery.

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MEDICAL

Better Purification and Recovery in Bioprocessing

Article | August 2, 2021

In the downstream portion of any bioprocess, one must pick through the dross before one can seize the gold the biotherapeutic that the bioprocess was always meant to generate. Unfortunately, the dross is both voluminous and various. And the biotherapeutic gold, unlike real gold, is corruptible. That is, it can suffer structural damage and activity loss. When discarding the dross and collecting the gold, bioprocessors must be efficient and gentle. They must, to the extent possible, eliminate contaminants and organic debris while ensuring that biotherapeutics avoid aggregation-inducing stresses and retain their integrity during purification and recovery. Anything less compromises purity and reduces yield. To purify and recover biotherapeutics efficiently and gently, bioprocessors must avail themselves of the most appropriate tools and techniques. Here, we talk with several experts about which tools and techniques can help bioprocessors overcome persistent challenges. Some of these experts also touch on new approaches that can help bioprocessors address emerging challenges.

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DIAGNOSTICS

Making Predictions by Digitizing Bioprocessing

Article | April 20, 2021

With advances in data analytics and machine learning, the move from descriptive and diagnostic analytics to predictive and prescriptive analytics and controls—allowing us to better forecast and understand what will happen and thus optimize process outcomes—is not only feasible but inevitable, according to Bonnie Shum, principal engineer, pharma technical innovation, technology & manufacturing sciences and technology at Genentech. “Well-trained artificial intelligence systems can help drive better decision making and how data is analyzed from drug discovery to process development and to manufacturing processes,” she says. Those advances, though, only really matter when they improve the lives of patients. That’s exactly what Shum expects. “The convergence of digital transformation and operational/processing changes will be critical for the facilities of the future and meeting the needs of our patients,” she continues. “Digital solutions may one day provide fully automated bioprocessing, eliminating manual intervention and enabling us to anticipate potential process deviations to prevent process failures, leading to real-time release and thus faster access for patients.” To turn Bioprocessing 4.0 into a production line for precision healthcare, real-time release and quickly manufacturing personalized medicines will be critical. Adding digitization and advanced analytics wherever possible will drive those improvements. In fact, many of these improvements, especially moving from descriptive to predictive bioprocessing, depend on more digitization.

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eHealth Innovation @ UHN

Our team improves quality of life by being the go-to place for developing cool and intuitive self-care and remote monitoring technologies for people with chronic diseases. We attract multidisciplinary talents including engineers, software developers, designers, project managers, and researchers. Leveraging our clinical connections with healthcare organizations globally, we develop technologies from users’ perspective, and evaluate our technologies to collect real data to assess their effectiveness and foster changes to better healthcare delivery.

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