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Aarthi Ramakrishnan

Hi, there! Thanks for visiting my website. I'm Aarthi, a Bioinformatician II at the Icahn School of Medicine at Mount Sinai. I analyze NGS datasets such as RNA-seq, ChIP-seq, ATAC-seq as well as use machine learning and deep learning models to analyze epigenetic datasets. My goal is putting my adept coding skills to use in finding cures for neurological diseases. My hobbies are reading books, writing and playing my piano.

Recent Posts

K-means clustering

I wanted to remind myself how the k-means clustering algorithm worked. Following are the steps involved in K-means clustering - 1. Start with a vector of 12 data points. For instance, [1, 2, 3, 4, 7, 8, 9, 10, 20, 21, 22, 23] 2. Randomly select 3 data points. These

K-means clustering

Interesting Bioinformatics Articles

Following is a collection of articles which I feel every Bioinformatician must be aware of. I will keep updating this list from time to time - 1. All biology is computational biology 2. Core services: Reward bioinformaticians 3. Importance of stupidity in scientific research

Interesting Bioinformatics Articles

The Art of Reading a Technical Paper

I came across an interesting Bioinformatics paper recently and wanted to read and understand it in its entirety. Reading the paper seemed intimidating at first, as the technical jargon that was being used seemed quite overwhelming. But reading a paper is not as difficult as it may first seem. Following

The Art of Reading a Technical Paper

Screen command in UNIX

Screen is a very useful command to have in your toolbox if you frequently use interactive sessions on your supercomputer logged in through a VPN. A VPN typically has a time limit, and you may get disconnected from it without any warning when you have poor internet connection. Screen program

Screen command in UNIX

Types of models in DESeq2

There are 2 major types of regression models one can specify in DESeq2 to explore the raw count matrices from an RNA-seq experiment - * Mean-reference model for Factors * Regression model for Covariates Mean-reference model for Factors - Factors typically represent categorical variable such as Gender, Ethnicity, Race etc. The mean-reference

Types of models in DESeq2