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Originally posted by AllSeq
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Brilliant move or sign of desperation on the part of Roche? After sending $60M+ down the drain with IBM they are now back to the big dance, now with (apparently) murky IP situation. ONT has licensed so much IP on the biochemistry side that it is not clear (to me) how Genia works around that. Judging from the patents that are now published, the sensors themselves are interesting but not terribly unique. The guys know their analog design (duh), but without biochemistry they will go nowhere. Maybe this is what Roche is banking on - take the platform and add their own biochemistry. -
Genia seems to be claiming two advantages:Originally posted by BBoy View Post
1) Precise control over the nanopore assembly process, allowing for 'better than Poisson' distribution
2) NanoTag biochemistry (being co-developed with Columbia and Harvard)
Do you not think this biochemistry confers an advantage (or are you saying they don't really 'own' it due to the murky nanopore IP situation)?Comment
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Their hardware, as much as can be judged from their patents and public presentations is elegant. Murky biochem IP is indeed the right way to characterize things. There are multiple startups, universities, and established companies working in this area, some with overlapping IP claims. It will be interesting to sit back and watch the lawyers get paid large amounts of money to argue about trivialities.Originally posted by AllSeq View PostComment
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I'm curious about this part as well. I wonder if Thermo Fisher dumped any ties with Genia after the Life acquisition?Originally posted by scbaker View PostComment
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Still haven't heard anything else about the group working on Starlight.Originally posted by snetmcom View Post
As for Thermo, my assumption is they still own a portion Genia and will make a bit of money on their investment once the acquisition closes.Comment
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Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
...Today, 11:10 AM -
Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.
There is no single reason why many patients don’t respond to treatment as expected. Cancer is...Yesterday, 05:17 AM -
Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.07-01-2026, 11:43 AM
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