Know Thy Complexities!!!!

Hi there!  This webpage covers the space and time Big-O complexities of common algorithms used in Computer Science.  When preparing for technical interviews in the past, I found myself spending hours crawling the internet putting together the best, average, and worst case complexities for search and sorting algorithms so that I wouldn't be stumped when asked about them.  Over the last few years, I've interviewed at several Silicon Valley startups, and also some bigger companies, like Yahoo, eBay, LinkedIn, and Google, and each time that I prepared for an interview, I thought to msyelf "Why oh why hasn't someone created a nice Big-O cheat sheet?".  So, to save all of you fine folks a ton of time, I went ahead and created one.  Enjoy!

Good

Fair

Poor

Interval tree and next generation sequencing

Recently I was working with some genome data on my leisure project. I had some huge number of coordinate of gene and various transcription element . The task was to fetch elements name  between the coordinate given by the required inputs range of the gene.

Though, the above problem challenge can be easily solved, using various approaches, but I wanted to have it best optimized way. Little R&D and small discussion with my programer cousin Najeeb,  I came across a data structure called "interval tree" .I decided to give a try and begin my exploration for this data structure.