Category Archives: Seminars

Why Publish lay claims of priority (historic and present) responsibility to communicate results back to the public reach a broader audience than people in the same field This talk not about tricks about editors and their task corresponding do’s and … Continue reading →

Intro slides from googling harvard examples (mostly with too much text) On bullets looks like a list, it’s not a list don’t let ppt drive the way you present information multiple topics — 5 or less. (can’t count more than … Continue reading →

Feature allocation, probability functions, and paintboxes Intro unsupervised learning canonical example, clustering what if objects are a part of multiple groups? feature allocation each group is now called a feature not a cluster Assumptions exchangeable finite number of features per … Continue reading →

Title: Quantification and Analysis of Intrinsic Variation in Gene Expression during Embryonic Development Alistair Boettiger Harvard University Abstract: The molecular scale interactions responsible for turning genes on and off have an inescapable degree of randomness — a consequence of their … Continue reading →

Background * PhD in Math from Oxford, undergrad at Princeton, started as a professor in business school at 24 * Met David Botstein to integrate in genetics and mathematics * Sydney Brenner on “omics” has created the idea that if … Continue reading →

Title: “Elucidating principles of gene regulation from stochastic models” Abstract: The complexity of multicellular organisms arises largely from reusing many of the same genes in numerous combinations, rather than by the introduction of novel genes for each new cell-type. Put … Continue reading →

lab running for ~6 months now. Introduction bacterial cell organization (in rod like cells): ends, middle, equally spaced ParM finds the ends by pushing — polymerizing until it starts bending. How bacteria grow cell wall holds shape. Digest this, get … Continue reading →

Background harvard undergrad, berkeley PhD, worked on Icecube (neutrino detection) Approach neural networks and support vector machines to score liklihood of particular outcomes (neutrinos or voter stats) Data collection — mass profile data from Facebook / Twitter. Campaign organization Tech … Continue reading →