On nucleosome positioning
May 13, 2008One of the topics I’ve been tracking with some interest lately has been nucleosome positioning. I’m going to briefly highlight some of my recent readings on the subject … Read the rest of this entry »
Archive for the 'Probabilistic models' Category
Predicting Drosophila Segmentation
February 28, 2008
Segal et. al. recently published a paper in Nature describing a computational framework that models transcriptional regulation in an attempt to predict expression. They apply their framework to the well characterized problem of segmentation of a Drosophila embryo. Read the rest of this entry »
Probabilistic Functional Networks
February 8, 2008
I recently read the Lee et. al. paper “A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans” in Nature Genetics. This is an extension of their previous work on building probabilistic functional networks to a multicellular organism (the worm). (Most of their prior work was in yeast.)
Alignment Uncertainty
January 25, 2008
Today in Science, Wong et. al. has a brief three page report entitled, “Alignment Uncertainty and Genomic Analysis”. In the same issue (pg 416; doi 10.1126/science.1153156) Rokas writes a perspective on Wong’s report. [Ironically, Rokas' perspective is probably near the same amount of text as Wong's report since Wong includes two large figures.]The report makes a simple assertion, “methods applied to the analysis of genomic data do not account for uncertainty in the sequence alignment.” They then show, by applying seven different popular alignment programs to protein sequences from seven yeast species, that uncertainty in the alignment can lead to problems, including different alignments giving different conclusions.
Morpheus Unbound
January 18, 2008A year ago, Arthur Lander published a review in Cell entitled “Morpheus Unbound: Reimagining the Morphogen Gradient”. It’s an articulate review of morphogen gradients — their formation, function, and regulation. He highlights the history of morphogen study and in so doing paints a picture of both how different perspectives have enriched the field and how it has evolved over time. It is a great read, heavily recommended.
