ML is fairly common in genomics, but for identifying predictive variables for cancer status, it's difficult. The training set is a matrix where rows are people (where some have cancer and some don't) and columns are genomic features (mutation, methylation, etc). You can easily have hundreds of thousands of features but getting even a thousand cancer patients enrolled in a study and sequenced is expensive and slow.
So, even though there are many "AI in biotech" companies out there, for predicting cancer status, most eventually end up hand crafting a small number of features based on extensive knowledge of cancer biology. The ML model tends to be simple and far less important than the features.
2. Liquid Biopsy -- many companies are working on diagnostic tests to detect cancer early, monitor treatment, detect recurrence, etc. Some of these products are already available but most are in R&D phase.
3. Immuno-Oncology -- the most promising development in cancer treatment in a long time. Successful tumors evade the immune system by essentially hiding themselves. Many companies are working on treatments to assist immune system in different ways. Some products have been in the market for a while now and have been pretty successful.
There is tremendous potential in Immuno-Oncology. I worked with umbilical cord blood [hematopoietic stem cell] transplants and this area really has tremendous potential for tech that only started being used in the late 80s to 90s. IMO much of the immediate potential for progress in software development will be with the legal and ux itself of ten tech though. Apart from a few companies the software is old, buggy, and has not or will be very slowly updated.
One idea that comes to mind is making vastly improved LIMS and electronic patient recodkeeping software, as what is presently being used [bbcs] is from the 80s although this could be accomplished with just a front end written for it.
I also have a difficult time reading large numbers without commas. Because I use Alfred (mac command launcher) quite a bit, I wrote up a simple workflow to re-display selected numbers with commas. Not as universal as the font-based solution but might be useful to some:
> For to accurately and repeatably describe positions
IMO, for most use cases, you don't need to describe positions; you provide something analogous to a SQL where clause.
Most querying in cell biology appears to content-based rather than coordinate-based. "drive down this artery 1000 cells" is not useful because your target might be 1010 cells down next week. Instead, you might say "drive down this artery until you find a cell with this particular receptor on the cell wall." Rather than keeping track of how many cells you've passed, you randomly bounce around the artery until you bind to a compatible receptor.
Good points. I'm coming from a pretty speculative direction where I'd want to enforce invariants, like: repair this tissue in-situ so that its thickness is always between x and y. Or make sure the density of this kind of cell in this region is at least A, and no more than B.
Basically, 3d modelling for tissue. How do you specify the reference model?
Actually, a 'debug' or 'dry-run' mode that simply prints out the git commands without running them would be useful for all kinds of users. Newbies can learn from it and pros can make sure that the commands are going to do what they expect it to. With git, I know what each command does but my concern with legit (and similar) is that the higher level commands might not do exactly what I think based on their name/description.
Racial disparity doesn't just result from racism or "like preferring like". There are many institutional and structural issues that are partially causal and a frank discussion could help uncover them as they relate to the startup world. Sadly, frank discussion of race is very difficult in this country.
Btw, I do agree that the valley is very meritocratic so I don't think racism is a big factor.
Space might be an issue but it's also strategic. I need the higher-resolution screens and have bought (and will continue to buy) the 15" versions even though I don't really need the better CPU or GPU. I'm sure there are many others like me who grudgingly or not will fork over the extra cash.
These people are supposed to be public servants. You would expect a special kind of person willing to make sacrifices for the greater good to take these jobs.
I would expect that pay and benefits should be pegged to the private sector. In some cases they could make more and some cases they could make less. But overall it should come close to private sector pay.
Average Compensation (2009)
Federal (123,049)
State & Local (69,913)
Private (61,051)
I'm not a big fan of public unions. It seems like there is nobody at the bargaining table on the side of the tax payer. Also, if people don't like the benefits that come with serving the public, they should not take the job. Like I said, it should take a special kind of person.
There's a pernicious assumption hiding there that public employees by definition must not deserve or earn their pay, whereas private employees doing the same work and making the same amount do.
Not really. It's completely fair for taxpayers to question the NPV of their employees (aka government workers).
Questioning it doesn't mean the NPV is negative. After all, private employers do this all the time. They decide a line of business provides an insufficient return on capital or doesn't fit the core, and they shut it down. Other times they find the NPV is awesome and pour on the investment. Since taxpayers are "the boss," this is completely appropriate.
If anything, the pernicious assumption runs precisely the opposite direction: that anyone who dare question the value to cost ratio of our bureaucratic overlords be attacked.
So, even though there are many "AI in biotech" companies out there, for predicting cancer status, most eventually end up hand crafting a small number of features based on extensive knowledge of cancer biology. The ML model tends to be simple and far less important than the features.