Pharmaceuticals & Biotechnology


Facial recognition is big tech's latest toxic 'gateway' app John Naughton

The Guardian

The headline above an essay in a magazine published by the Association of Computing Machinery (ACM) caught my eye. "Facial recognition is the plutonium of AI", it said. Since plutonium – a by-product of uranium-based nuclear power generation – is one of the most toxic materials known to humankind, this seemed like an alarmist metaphor, so I settled down to read. The article, by a Microsoft researcher, Luke Stark, argues that facial-recognition technology – one of the current obsessions of the tech industry – is potentially so toxic for the health of human society that it should be treated like plutonium and restricted accordingly. You could spend a lot of time in Silicon Valley before you heard sentiments like these about a technology that enables computers to recognise faces in a photograph or from a camera.


Hitting the Books: How calculus is helping unravel DNA's secrets

Engadget

Welcome to Hitting the Books. With less than one in five Americans reading just for fun these days, we've done the hard work for you by scouring the internet for the most interesting, thought provoking books on science and technology we can find and delivering an easily digestible nugget of their stories. Calculus has provided humanity a window into the inner workings of the world around us since the fateful day Isaac Newton got conked by a falling apple. But we've only ever really applied these mathematical tools to our "hard" sciences, like physics or chemistry. Heck, we probably wouldn't have discovered Neptune if not for calculus.


Folding Secrets of Protein Unlocked by Artificial Intelligence

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Proteins are crucial to almost every fundamental biological process necessary for life. They do everything from create and maintain the shape of cells to serving as both signal and receiver for cellular communications. Proteins are composed on long chains of amino acids and they perform their varied tasks by folding themselves into precise 3D structures that determine how they function and interact with other molecules. Because their exact shape is so crucial to their function research into uncovering the exact shape is a central task to molecular biology. This task is especially important for the development of lifesaving and life-altering medicines.


How our gray matter tackles gray areas

MIT News

When Katie O'Nell's high school biology teacher showed a NOVA video on epigenetics after the AP exam, he was mostly trying to fill time. But for O'Nell, the video sparked a whole new area of curiosity. She was fascinated by the idea that certain genes could be turned on and off, controlling what traits or processes were expressed without actually editing the genetic code itself. She was further excited about what this process could mean for the human mind. But upon starting at MIT, she realized that she was less interested in the cellular level of neuroscience and more fascinated by bigger questions, such as, what makes certain people generous toward certain others?


Global Artificial Intelligence Conference on April 23rd to April 25th in Seattle GlobalBigDataConference

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Global Big Data Conference's vendor agnostic Global Artificial Intelligence(AI) Conference is held on April 23rd, April 24th, & April 25th 2019 on all industry verticals(Finance, Retail/E-Commerce/M-Commerce, Healthcare/Pharma/BioTech, Energy, Education, Insurance, Manufacturing, Telco, Auto, Hi-Tech, Media, Agriculture, Chemical, Government, Transportation etc..). It will be the largest vendor agnostic conference in AI space. The Conference allows practitioners to discuss AI through effective use of various techniques. Large amount of data created by various mobile platforms, social media interactions, e-commerce transactions, and IoT provide an opportunity for businesses to effectively tailor their services by effective use of AI. Proper use of Artificial Intelligence can be a major competitive advantage for any business considering vast amount of data being generated.


Response to Comment on "Ghost cytometry"

Science

Di Carlo et al. comment that our original results were insufficient to prove that the ghost cytometry technique is performing a morphologic analysis of cells in flow. We emphasize that the technique is primarily intended to acquire and classify morphological information of cells in a computationally efficient manner without reconstructing images. We provide additional supporting information, including images reconstructed from the compressive waveforms and a discussion of current and future throughput potentials. Ghost cytometry (GC) performs a direct analysis of compressive imaging waveforms and thereby substantially relieves the computational bottleneck hindering the realization of high-throughput cytometry based on morphological information (1). The comments by Di Carlo et al. argue against a number of our conclusions (2), but given the restricted length allowed for this response, we will address what we consider the most important points.


Comment on "Ghost cytometry"

Science

Ota et al. (Reports, 15 June 2018, p. 1246) report using pseudo-random optical masks and a spatial-temporal transformation to perform blur-free, high–frame rate imaging of cells in flow with a high signal-to-noise ratio. They also claim sorting at rates of 3000 cells per second, based on imaging data. The experiments conducted and results reported in their study are insufficient to support these conclusions. Ota et al. (1) proposed an approach to perform image-based flow cytometry and cell sorting that has attracted substantial attention because high throughput ( 3000 cells/s) and a high signal-to-noise ratio (SNR) were claimed. For example, on the basis of these assertions, the introductory commentary (2) referred to the system as an "ultrahigh-speed fluorescence imaging–activated cell sorter."


IBM Watson Health cuts back Drug Discovery 'artificial intelligence' after lackluster sales

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IBM Watson Health is tapering off its Drug Discovery program, which uses "AI" software to help companies develop new pharmaceuticals, blaming poor sales. IBM spokesperson Ed Barbini told The Register: "We are not discontinuing our Watson for Drug Discovery offering, and we remain committed to its continued success for our clients currently using the technology. We are focusing our resources within Watson Health to double down on the adjacent field of clinical development where we see an even greater market need for our data and AI capabilities." In other words, it appears the product won't be sold to any new customers, however, organizations that want to continue using the system will still be supported. When we pressed Big Blue's spinners to clarify this, they tried to downplay the situation using these presumably Watson neural-network-generated words: The offering is staying on the market, and we'll work with clients who want to team with IBM in this area.


Scientists create programmable circuits in human cells that could lead to 'biocomputers'

Daily Mail

Researchers say they've successfully created a more powerful computer-like human cell that could eventually be used to help monitor one's health or even fight against cancer and other illnesses. Using the gene-editing tool CRISPR-Cas9, researchers were able to model a human cell after a computer and make what they are referring to as a'program scalable circuits.' 'This cell computer may sound like a very revolutionary idea, but that's not the case," said Martin Fussenegger, Professor of Biotechnology and Bioengineering at the Department of Biosystems Science and Engineering at ETH Zurich in Basel. 'The human body itself is a large computer. Its metabolism has drawn on the computing power of trillions of cells since time immemorial.'


PhD student in machine learning and computational biology University of Helsinki

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The Institute for Molecular Medicine Finland (FIMM) is an international research unit focusing on human genomics and personalised medicine at the Helsinki Institute of Life Science (HiLIFE) of the University of Helsinki - a leading Nordic university with a strong commitment to life science research. FIMM is part of the Nordic EMBL Partnership for Molecular Medicine, composed of the European Molecular Biology Laboratory (EMBL) and the centres for molecular medicine in Norway, Sweden and Denmark, and the EU-LIFE Community. A PhD student position is available in the research group of FIMM-EMBL Group Leader Dr. Esa Pitkänen at the Institute of Molecular Medicine Finland (FIMM), University of Helsinki. The research group will start at FIMM in July 2019, and will address data integration, analysis and interpretation challenges stemming from massive-scale data generated in clinical and research settings. We will work closely with interdisciplinary collaborators at University of Helsinki, Helsinki University Hospital, EMBL and German Cancer Research Center.