Mark Gerstein

TL;DR: A Bayesian statistical analysis algorithm for the detection of CNVs from both types of genomic data and can be seen as a technique to refine CNVs identified by fast point-estimate methods and also as a framework to integrate array-CGH and sequencing data with other CNV-related biological knowledge, all through informative priors.

TL;DR: The chapter explains the way structural features in the motions database can be related to sequence, an important part of the overall process of transferring annotation to uncharacterized genomic data, which allows determination of a sequence-propensity scale for amino acids to be in linkers in general or flexible hinges in particular.

TL;DR: It is found that nonspecific binding by MM oligos depends upon the individual nucleotide substitutions they incorporate: C→A, C→G and T→A (yielding purine-purine mispairs) are most disruptive, whereas A→X were least disruptive.

TL;DR: Reanalyze the evidence used by CHESS, and it is found that nearly all protein-coding predictions are false positives, and that 86% overlap transposons marked by RepeatMasker that are known to frequently result in false positive protein- coding predictions.

TL;DR: DeepVelo as mentioned in this paper is a neural network-based ordinary differential equation that can model complex transcriptome dynamics by describing continuous-time gene expression changes within individual cells and identify developmental driver genes via perturbation analysis.