Recently, a member of this community suggested investing in Homology Medicines Inc which trades under the symbol "FIXX." It is a gene editing company with several "Buy" ratings.
Today, it was announced the following insiders have sold shares in $FIXX.
- Arthur Tzianabos sold 5354 shares
- Timothy Kelly sold 1406 shares
- Albert Seymour sold 1661 shares
- W. Bradford Smith sold 2182 shares
- Gabriel Cohn sold 1661 shares
Stock Launchers is not covering this company. The above report of insider selling is merely for your information and edification.
Researchers from The University of Edinburgh and Oxford propose a GNN model (Dist2Cycle) for localizing homological information in the form of distance functions between each point on complex to its nearest homology generating feature.
Since homology-related information is contained in its null space, the research team focused on the subspace spanned by eigenvectors corresponding to the lowest values (eigenvalues) instead of using the most significant ones (eigenvectors) of the relevant Laplacian operator. The research group implemented this method by calculating the most-significant subspace of an inverted version of their operator, which they believe is more optimal than traditional ones.
Quick Read | Paper | Github
https://preview.redd.it/6tmwvuos8jw71.png?width=1392&format=png&auto=webp&s=9e2e3ded8913f2081ccc41b5c86396dbd6a87c9c
Hello,
I have some proteins with blast homologs, and I am trying to get a quantitative measure of the representativeness of each match. As I understand, everyone normally compares blast alignments using bit scores, as these are database-size independent. However (please correct me if I'm wrong) bit-scores only describe the quality of the HSP itself, not how representative that HSP/bit score is of it's parent protein.
Would I be barking up the wrong tree if I DIYed a score for comparison? One of the main reasons I'm asking is I'm not particularly hot on BLAST statistics (so this may all be unnecessary) and I know making up your own stats can be a bad idea.
My score would be something like:
(bitscore * hit_perc_coverage) / log (evalue)
This would hopefully approximate to:
(quality of HSP * HSP representativeness of protein) / reliability of HSP quality
NB - I would take the log to stop differences in E-value massively biasing the final score.
Thanks for reading!
EDIT
Having thought about it a bit more, dividing by the log of the e-value would decrease the overall score when the e-value has larger absolute exponents (i.e. when the e-value decreases, assuming the e-value is below 1). I think this would be bad, as smaller/better e values would give smaller final scores than larger/worse e values, but you would be looking for higher scores being better from the perspective of the coverage/bit score. This means a better (but potentially still crap!) score would likely be something more like:
bitscore * hit_perc_coverage * log (evalue)
"With today’s milestone, we have also accomplished our goal of having three clinical programs by the end of 2021."
FIXX -2.82 %, $6.03, near all time lows, in afternoon trading. Short interest has declined to 5.5% of float.
Which means the simplicity complex is {p0,p1, (p0p1)} I tried to find Z_(K), is it set Z (integer)? I did this so far https://pasteboard.co/zI1hsBI43tj2.jpg
hi r/medicine
I've been looking into mutations and genetic homology between variants of the coronavirus for a non-academic article i'm writing but I can't seem to find exact numbers on the degree of genetic homology between the wuhan strain and, for example, the delta strain. Does anyone have any resources on this, or advice on where to look?
Thanks!
$FIXX Homology Medicines stock with a bottom breakout watch above 7.55 , see https://stockconsultant.com/?FIXX
FIXX Homology Medicines stock chart
#investing #stocks #wallstreet #stockmarket #money
Hi everyone,
I'm doing my master thesis in algebric-topology and I want to delve into persitence homology.
Until now I'v always used coeficients in Z_2, and I want to understand the basis with coefficient in Z. Has anyone got any decent book or paper explaining that part?
Can anyone please suggest me how to search for a target protein to perform homology modeling?....I have no clue in this and I am just starting this brand new for a project. I would greatly appreciate your help.
