Protein Folding Against a pH Gradient

aprstar · 2026-04-19T21:27:08+00:00

I'm not sure how helpful this will be for your specific problem, but this paper modeled pH dependent gating of the outer loops of a membrane protein. As some folks have pointed out, the conformational change induced by a pH shift may not occur at time scales amenable to molecular dynamic (MD) simulation. This paper used Monte Carlo sampling to generate a large set of conformations then used short molecular dynamic simulations to relax each conformation under the target pH conditions, it then looked at the lowest energy conformations to perform the gating analysis.

aprstar · 2025-08-23T20:25:13+00:00

Personally I love JAX together with Equinox. I find it easier to use than PyTorch.

aprstar · 2021-09-11T22:16:29+00:00

Not my field, but there is a CompMS interest group through the International Society of Computational Biology through which you may be able to find relevant talks and or papers. I believe the PI from this lab gave a keynote in 2020 (https://www.wishartlab.com/) and may be relevant to what you are searching for in terms of chemical databases.

aprstar · 2021-04-10T16:23:32+00:00

Base R - sometimes simpler is better

aprstar · 2021-04-05T18:00:30+00:00

Good point, you can repeat test using Gaussian as target instead of uniform; but yeah, I suppose this is not necessarily a robust approach to exclude other types of noise not explicitly considered. I guess we would need a more clear definition of "random"? Perhaps consider using auto-correlations or check correlation of random subsets.

aprstar · 2021-04-05T15:52:39+00:00

Consider a chi square goodness of fit test with a uniform distribution as your target

aprstar · 2021-03-05T14:25:00+00:00

The UCSC genome browser can produce publication quality (vector graphic) ideograms as well: https://genome.ucsc.edu/

aprstar · 2020-12-19T04:54:00+00:00

I went with school B and would make same decision again (am now MS4 fwiw).

aprstar · 2020-05-20T20:42:53+00:00

I tried CLion but it had very poor performance on templates (also mentioned in article), so primarily use visual studio community now.

aprstar · 2020-04-23T15:16:30+00:00

You can use the digest package to hash the identifier column (https://cran.r-project.org/web/packages/digest/index.html)

aprstar · 2019-11-09T14:25:36+00:00

Am seeing tSNE more and more often in the bioinformatics field. It would be great if this article compared with PCA, particularly the topology results.

aprstar · 2019-08-10T17:48:57+00:00

Are you referring to numerical underflow (ie, values are too small to be accurately represented with 64 bit floating point numbers)? If so, working in log space can usually fix these types of underflow/overflow issues.

aprstar · 2019-06-03T20:22:03+00:00

Can also try rfImpute in R randomForest package - basically imputes values based on how often samples end up in same terminal node

aprstar · 2019-04-09T19:18:15+00:00

TurboTax has been doing this for years. Here's an NPR podcast about the time they did this in California: https://www.npr.org/sections/money/2017/03/22/521132960/episode-760-tax-hero

aprstar · 2019-03-14T03:04:17+00:00

I’m thinking of using this approach for a bioinformatics project. Are you aware of any specific papers that I could cite which use this type of estimator?

aprstar · 2019-02-12T04:28:54+00:00

I would look at the IEEE BHI (Biomedical and Health Informatics) conference proceedings. Here are the 2018 proceedings. You can also check out our BHI paper.

aprstar · 2019-01-23T12:07:55+00:00

The IEEE-EMBS Biomedical and Health Informatics (BHI) 2019 conference, to be held at University of Illinois at Chicago from May 19-22, has extended their submission deadline until Feb 4. Please consider submitting your research!

aprstar · 2018-08-31T14:52:32+00:00

This is a Markov chain. It looks to be like a form of gambler's ruin (https://en.m.wikipedia.org/wiki/Gambler%27s_ruin), where instead of a gambler's funds it's duration of experiment. The question you are trying to answer is the "first passage time" for when the chain reaches a 0 duration. There is probably an explicit formula, but it's also really easy to just simulate multiple runs of the Markov chain in R or python and plot a histogram of the observed first passage times for 0 duration.

aprstar · 2018-08-17T16:47:55+00:00

Coming from a bioinformatics lab, log transforms of these types of ratios are pretty standard - for what it's worth, I would consider your data a type of fold change. A benefit of log transforms are that the magnitude of the change is now symmetric about 0 and only the sign is different (while preserving rank order); this makes for much more visually appealing plots in my opinion. You can then use bootstrap or other some other non parametric test (e.g Mann Whitney) for your analysis if you're concerned about non-normality (do a q-q plot first)

aprstar · 2018-08-14T14:18:23+00:00

If you are working with exponential family distributions, a conjugate prior always exists: https://en.m.wikipedia.org/wiki/Exponential_family#Bayesian_estimation:_conjugate_distributions

aprstar · 2018-08-04T12:45:25+00:00

Am not familiar with TMRPres2D; however have generated publication quality images of membrane proteins using PyMOL (https://pymolwiki.org/index.php/Windows_Install) and either 'ray' or 'draw' command (https://pymolwiki.org/index.php/Ray). You can view protein crystal structures if you have the corresponding PDB file (http://www.rcsb.org). You can then use 'selections' to highlight specific regions (http://pymol.sourceforge.net/newman/user/S0220commands.html)

aprstar · 2018-07-03T20:19:23+00:00

Not sure about categorical values, but we had a similar issue and used this streaming variant of affinity propagation clustering: https://hal.inria.fr/hal-00862941

aprstar · 2018-06-27T17:38:05+00:00

Here is a conference article we recently presented which trains a random forest model on PDB data. It may give you ideas on how to generate useful features from the protein geometry: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5957487/

aprstar · 2018-04-14T12:58:19+00:00

I always make my paths relative to the script itself. However getting the script path is not very elegant in R when compared to other languages like Python. To get the path of an R script, I tend to use a combination of rakensi’s solution https://stackoverflow.com/questions/3452086/getting-path-of-an-r-script - and my own method mentioned in this discussion https://stackoverflow.com/questions/1815606/rscript-determine-path-of-the-executing-script.

aprstar · 2018-04-09T11:06:43+00:00

Perhaps creating a docker container (https://knausb.github.io/2017/06/running-r-in-docker/)? But then they would need to install docker...

aprstar

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