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I'm a PhD candidate in Medical Biophysics at the University of Toronto studying epigenetics and cancer. Math and physics background taking a step into bioinformatics and evolution

Thanks to everyone who has helped me get here and I wish you all the luck in your future endeavours!

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It has been a privilege to work with so many talented and hard-working colleagues and, I appreciate the mentorship from my supervisor,, and am grateful for how much I have learned from my committee members and Dr. John Dick.

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After many years, I'm delighted to say that I am finally !

I've written a few thoughts that I'd like to share with people about the whole experience.

Just discovered this excellent online textbook/gitbook "Computational Genomics with R":
principle author/editor Altuna Akalin

I'm delighted to share that my paper with and is out today in Cancer Research!

We use Hi-C in primary tumours to investigate how the 3D genome is altered, or not, in prostate cancer. Congrats and thanks to all of my co-authors.

For a guided breakdown of this paper that's aimed at a broader audience, here's an accompanying blog post:

We hope you enjoy the paper and are happy to discuss this work with anyone.

machine learning, safety 

This is a great video summarizing some issues with machine learning models in production.

tl;dr when there are distributional shifts between training and real world data, some models can still be capable of doing what you want but implicitly learn the wrong objective. In the end, they don't do what you want and can do precisely what you don't want. This can happen even if you specify objectives accurately and perform safety checks along the way.

> I am pleased to inform you that your above-referenced manuscript has been accepted for publication in Cancer Research.

Just got confirmation that my paper got accepted today and should be published with a few weeks! I'm happy to see that out, it's been a long time coming.

hit another website that is absolutely essential and only seems to work in Chrome.

I'm livid.

This is insane.

This is straight out of the late 1990s. There are no more Web standards? Only reliance on one browser from one megacorp?

Didn't we learn anything from the past 30 years?

For org-mode users, native citation support is here!

This looks fantastic with a very simple syntax. I'm looking forward to using this.

Today I finally got provisional acceptance of my paper! Still some work to do, but nice that I know this paper is going to be done

work in progress. simple graphical interface to view files:

+ written in c, because their graphics library is easy to use.
+ can filter by tags. tags have to be assigned in the bibtex file.
+ can export a single reference to bibtex format and formatted text.
+ to do: capability to filter by document type.
+ to do: open file by clicking on it, using the plumber.

things i don't need/want:
+ looking up citations online, cloud storage.

@mattcen @lm @zgxn @cadadr

Zotero has lots of great features, and is good with generating bibtex with the Better BibTeX plugin ( That's what I've been shifting to. ebib is great in Emacs, and that's what I've used before. There's also jabref, which I used a long time ago.

I started my work/academically-oriented website years ago with no real plans for it. But I kept writing stuff for it, mostly for my own benefit. Now I've been getting emails from people saying they're reading it, have learned something from the stuff I've written. Some have even pointed out issues in some of my code and I've worked to fix it.

It's not much, but it feels good having written something people find useful. Small victories!

If you ever want a crash course in bad web design, try submitting a journal article or asking for access to data from an institution. Few things bug me more than trying to fill out these absolutely horrendous online web forms.

Are there any good books on how to do beautiful layout in LaTeX? I have most of the Addison Wesley / Pearson / InformIT books but wondered if there was some brave soul out there that has something more like a tutorial of not only "put these commands here to make this work" but also goes into the "why" of the design they chose.

(Note: this is a specific question for a specific item. Alternatives are not requested. Spitballing web searches are not helpful. I want an artifact, not Stack Overflow).

They don't throw a ton of data at you because they don't even need a lot of experiments.
It's just a careful, mathematically-based, and biologically-inspired analysis with clearly stated conclusions.

More of this, please.

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Instead of relying on a trendy idea in the field, they slow down, develop toy models of gene regulation based on existing literature, explore how these models might function, then make the models more complex as needed.

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It's so refreshing to see a paper like this one by Xiao, Hafner, and Boettiger treat the conflicting observations about TAD perturbations and enhancer-promoter contacts seriously.

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