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New question for tablet owners: do you read epubs on it? Where do you obtain eBooks in DRM-free epub format?

This paper was a pleasure to read.

Identifying recurrent genetic variants in a rare disease, recreating the phenotype in mice, investigating the epigenetics and 3D chromatin, and functional investigation of the mechanism.

Papers like these are great

Hi, I'm Ilhan. I'm a fluid mechanician currently working on computational hydrology. I'm interested in environmental and geophysical flow modeling.

Quickly building your own conda packages with `conda build` and `conda skeleton`

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Cleaning your packages folder for faster dependency solving with `conda clean`

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Exporting/importing environments with `conda env export --no-builds > environment.yaml` and `conda env create -n <NAME> -f environment.yaml`

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Revisions of environments with `conda list --revisions` and `conda install --revision`

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From many conversations I've had with people, I've compiled a list of pragmatic tips for using . I hope people find them useful

Let me know if these are useful, or there are other great tips you love to share with people!

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A new blog post about software development in computational biology!

Some thoughts on how developers can make computational biologists' lives easier by defaulting to making statically-linked, binary applications. This can help with speed, ease of use, and ease of installation, which are all highly prized by end users

I really like this analysis of the values behind different text editors.

I have felt the impact of these different value systems on the tools themselves, which also mirrors the different places I use them.

This seems like a pretty good attempt to replicate some of the mathematical methods of in .

Does anyone have experience trying to use a package like this for complex computational work in rust?

So today on the bioinformatics chat podcast we're excited to have Xiang Ji himself! We start with a bit of background on phylogenetics and then go into the why and how of the gradient calculation.

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We performed Hi-C sequencing in frozen prostate tumours, combined our data with other genetic, transcriptomic, and epigenetic data on the same tumours, and investigated how mutations in prostate cancer rewire the genome and affect gene expression genome-wide.

We hope that these biological and technical insights will enable better characterization of patient tumour samples and give more insight into the assaults to the genetic architecture in cancer

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I'm happy to share the preprint for recent work led by myself and looking at the 3D genome in prostate cancer as it goes into peer review.

"Cis-Regulatory Element Hijacking by Structural Variants Overshadows Topological Changes in Primary Prostate Cancer" is available on bioRxiv, now.

I was planning on submitting a paper today. Two days ago my 11 year old motherboard crashed and corrupted my OS on my hard drive.

I have code saved on GitHub, big files and figures saved on OneDrive, and made 2 separate backups of my data.

48 hours and a new CPU + motherboard later, I have all of my data back and am up and running.
Still on track to submit today.

You know how people always say back up your data? Listen to those people


Overall, the conclusion of "detection rates are much lower than we'd like" is probably true, but is something already discussed without this paper. The numbers in this paper are tough to assess because there is little empirical evidence, and the empirical evidence they do have don't necessarily align with their predictions.

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On the flip side, for smaller regions, the confidence intervals are smaller, but these don't match well with the serological estimates. Half of the regions have model predictions that don't align with the serological studies.
So there are important discrepancies between this model and independent experiments that need to be resolved.

Importantly, these discrepancies are always less than the empirical data. Meaning the model may predict fewer infected individuals than there actually are.

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