Author Archives: ashish
Abstract There has been great interest in creating probabilistic programming languages to simplify the coding of statistical tasks; however, there still does not exist a formal language that simultaneously provides (1) continuous probability distributions, (2) the ability to naturally express … Continue reading
I’ve been having a great time at ICFP in Tokyo. I spent the first day at the ML Workshop, and am now enjoying CUFP after presenting my own tutorial on creating collaborative scientific software in OCaml.
Baba Brinkman’s Rap Guide to Evolution is a hilarious show on a serious topic. It’s an alternative approach to educate people about the fact of evolution. If you have it, don’t miss the chance to see him live!
“programmers should not be puzzle-minded …. We would be much better served by clean, systematic minds, with a sense of elegance.” — Dijkstra (In interview as reported in CACM)
The CRIT framework for identifying cross patterns in systems biology and application to chemogenomics
Abstract Biological data is often tabular but finding statistically valid connections between entities in a sequence of tables can be problematic – for example, connecting particular entities in a drug property table to gene properties in a second table, using … Continue reading
I just registered for the OCaml User Meeting. Looking forward to seeing everyone in Paris. I’ll also attend the OCaml Hacking Days at IRILL and visit OCamlCore.
A bug was introduced in MACS 1.4, which arises if many of the initial reads in an input SAM file are unaligned. You are having this error if MACS is printing something like the following to stderr: Traceback (most recent … Continue reading
Here’s a simple C program that demonstrates the use of the pthreads library. The following code can be downloaded here, so you can test it yourself. Simply compile with the command: gcc -lpthread pthreads_test.c -o pthreads_test First, let’s import some … Continue reading
Downloading MACS requires you to either sign up for their mailing list or solve a puzzle. I signed up for their mailing list and then solved the puzzle for fun. Perhaps you will find the answer on my website.
Prediction and characterization of noncoding RNAs in C. elegans by integrating conservation, secondary structure, and high-throughput sequencing and array data
Abstract We present an integrative machine learning method, incRNA, for whole-genome identification of noncoding RNAs (ncRNAs). It combines a large amount of expression data, RNA secondary-structure stability, and evolutionary conservation at the protein and nucleic-acid level. Using the incRNA model … Continue reading