Greg Bedwell
@gbedwell.bsky.social
Protein chemist, computational biologist, and general data enthusiast. Big fan of good food, sports, travel, and books. gbedwell.github.io
Promising too much and failing to deliver could also have negative consequences related to public perception of the effort, etc. I absolutely agree about Aim 2B, but given the current anti-science/anti-knowledge climate in the US, a more measured/balanced spin seems responsible.
April 21, 2025 at 11:24 PM
Promising too much and failing to deliver could also have negative consequences related to public perception of the effort, etc. I absolutely agree about Aim 2B, but given the current anti-science/anti-knowledge climate in the US, a more measured/balanced spin seems responsible.
Very cool paper! The portal of P22 also appears to act as a pressure-sensitive switch/signal transmitter during packaging, though in a seemingly different way to P74-26. P74-26 is a very cool model system -- taking extremes (dsDNA packaging) to another level (at high temps)! Incredible machines.
April 18, 2025 at 10:12 PM
Very cool paper! The portal of P22 also appears to act as a pressure-sensitive switch/signal transmitter during packaging, though in a seemingly different way to P74-26. P74-26 is a very cool model system -- taking extremes (dsDNA packaging) to another level (at high temps)! Incredible machines.
ntCard (github.com/bcgsc/ntCard) is also supposed to be fast and accurate (moreso than khmer, I believe). Both, however, utilize cardinality estimations. You may want exact numbers.
GitHub - bcgsc/ntCard: Estimating k-mer coverage histogram of genomics data
Estimating k-mer coverage histogram of genomics data - bcgsc/ntCard
github.com
January 30, 2025 at 6:02 PM
ntCard (github.com/bcgsc/ntCard) is also supposed to be fast and accurate (moreso than khmer, I believe). Both, however, utilize cardinality estimations. You may want exact numbers.
I've done similar calculations with github.com/dib-lab/khmer (see: unique-kmers.py). khmer itself might also be far more complicated than what you were after, however.
GitHub - dib-lab/khmer: In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more
In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more - dib-lab/khmer
github.com
January 30, 2025 at 5:57 PM
I've done similar calculations with github.com/dib-lab/khmer (see: unique-kmers.py). khmer itself might also be far more complicated than what you were after, however.
Only lentiviruses are known to infect non-dividing cells, suggesting that only they are likely to have evolved mechanisms of nuclear import.
January 17, 2025 at 6:00 PM
Only lentiviruses are known to infect non-dividing cells, suggesting that only they are likely to have evolved mechanisms of nuclear import.
As Gregorio Weber famously stated, “Indeed the protein molecule model resulting from the X-ray crystallographic observations is a ‘platonic’ protein, well removed in its perfection from the
kicking and screaming ‘stochastic’ molecule that we infer must exist in solution.”
kicking and screaming ‘stochastic’ molecule that we infer must exist in solution.”
November 25, 2024 at 11:47 PM
As Gregorio Weber famously stated, “Indeed the protein molecule model resulting from the X-ray crystallographic observations is a ‘platonic’ protein, well removed in its perfection from the
kicking and screaming ‘stochastic’ molecule that we infer must exist in solution.”
kicking and screaming ‘stochastic’ molecule that we infer must exist in solution.”
Reposted by Greg Bedwell
Alphafold and various materials modeling techniques are some of the best algorithmic probability generators out there, today, and I really wish we hadn't let these hypemerchants collapse and conflate GPTs, LLMs, ML, NLP, and Algorithms into an undifferentiated smear they labeled "AI"
August 5, 2024 at 5:56 AM
Alphafold and various materials modeling techniques are some of the best algorithmic probability generators out there, today, and I really wish we hadn't let these hypemerchants collapse and conflate GPTs, LLMs, ML, NLP, and Algorithms into an undifferentiated smear they labeled "AI"