chrisprobert

9 ms·

1.
Robust and Efficient Tissue Segmentation for Digital Pathology(conflux.xyz)
4 points by chrisprobert 2y ago|0 comments
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Data Science Workflows at insitro using redun on AWS Batch(aws.amazon.com)
1 points by chrisprobert 5y ago|0 comments
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Space Shuttle Launch Abort Modes(en.wikipedia.org)
3 points by chrisprobert 7y ago|0 comments
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by chrisprobert 8y ago
insitro | Machine Learning for Drug Discovery | South San Francisco, CA | Full Time | Onsite insitro is reinventing drug discovery by bringing cutting-edge machine learning in a closed loop with our high throughput robotic biology data fact
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by chrisprobert 8y ago
I'm curious whether this is backed by Google File System ( https://static.googleusercontent.com/media/research.google.c... ), or something else.
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by chrisprobert 8y ago
What's interesting about this approach (TIL expansion) relative to other leading cellular immunotherapy approaches (CAR-T/NK and TCR) is that it doesn't rely on gene editing. Long term, I think genetically "programmable&
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by chrisprobert 9y ago
Coupa Cafe on Ramona St. in Palo Alto, or the one in Y2E2 at Stanford.
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by chrisprobert 9y ago
Totally agree!
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by chrisprobert 9y ago
Announcing TensorFlow's new development roadmap mandate: copy everything PyTorch is doing :-)
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by chrisprobert 9y ago
Great to see this coming from a team with such a solid AI background!
11.
Jeff Huber Steps Down as GRAIL's CEO(cnbc.com)
1 points by chrisprobert 9y ago|0 comments
12.
DeepLIFT: new method for interpreting deep neural networks(arxiv.org)
2 points by chrisprobert 10y ago|0 comments
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Apply HN: Artisanal Genomics
2 points by chrisprobert 10y ago|0 comments
14.
by chrisprobert 11y ago
I would put > 50/50 odds on there being a human alive today with at least one CRISPR-edited germline variant. I think the question is now how can we regulate/control CRISPR germline editing; not how can we prevent it. Human emb
15.
Genetics: Big hopes for big data - using genomic data to transform cancer care(nature.com)
1 points by chrisprobert 11y ago|0 comments
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by chrisprobert 11y ago
Key question for digital health / biotech startups is whether direct to consumer (D2C) advertising for testing services (e.g. genetic carrier screening; cancer risk screening) would be included.
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by chrisprobert 11y ago
Correct - their current v4 chip covers ~602K SNPs and they have > 1 M customers, so you couldn't uniquely identify all of them by genotype. But given the frequency of rare variation in humans, you'd expect to be able to reduce
18.
by chrisprobert 11y ago
You're right that Ancestry.com is focused on mtDNA, but 23andMe actually uses a custom Illumina microarray with autosome, allosome, and mitochondrial targets. Here's a study where 23andMe used their (old version) chips to replicat
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AtomNet: A Deep Convolutional Neural Network for Drug Discovery(arxiv.org)
5 points by chrisprobert 11y ago|3 comments
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by chrisprobert 11y ago
Totally agree here - would be easy to fabricate DNA oligos with given mtDNA or STR sequences, especially if you know forensic investigators are only going to use very small target sequences for identification purposes. This could be a case
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by chrisprobert 11y ago
Good question. This problem affects multiple steps of a NGS-based forensics product: sample collection, DNA extraction, library preparation, the sequencing itself, alignment/assembly, and statistical variant interpretation all have pot
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by chrisprobert 11y ago
This article brings up problems with current PCR-based STR genotyping methods, but lacks information about technologies that are competing to be the future of forensic genotyping. Here's some more context on the NGS technologies that a
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Illumina funds Helix with $100M – personalized genomic information(techcrunch.com)
2 points by chrisprobert 11y ago|0 comments
24.
by chrisprobert 12y ago
I also enjoyed his post on the "Two Cultures of Computing": http://pgbovine.net/two-cultures-of-computing.htm Definitely something worth thinking about as we build tools for other developers/engineers to use.