A Probabilistic Time Series Model for Gene Regulatory Relationships and Learning the Model from Gene Expression Data Learning Causal Networks from Gene Expression Data.

They would lead me to opportunities otherwise hidden to a person of my upbringing, and they'd come to my aid when I failed, as we all do on occasion. That aid was never in more dire need than during my first job out of business school at Deloitte & Touche Consulting. By conventional standards, I was an awful entry-level consultant. Put me in front of a spreadsheet and my eyes glaze over, which is what happened when I found myself on my first project, huddled in a cramped windowless room in the middle of suburbia, files stretching from floor to ceiling, poring over a sea of data with a few other first-year consultants. I tried; I really did. But I just couldn't. I was convinced boredom that bad was lethal. I was clearly well on my way to getting fired or quitting. Luckily, I had already applied some of the very rules of networking that I was still in the process of learning. In my spare time, when I wasn't painfully attempting to analyze some data-ridden worksheet, I reached out to ex-classmates, professors, old bosses, and anyone who might stand to benefit from a relationship with Deloitte ...»