Variational Infinite Heterogeneous Mixture Model for Semi-supervised Clustering of Heart Enhancers.

Mehdi TF, Singh G, Mitchell JA, Moses AM

Bioinformatics 2019 Feb 07; ():

PMID: 30753279

Abstract

Mammalian genomes can contain thousands of enhancers but only a subset are actively driving gene expression in a given cellular context. Integrated genomic datasets can be harnessed to predict active enhancers. One challenge in integration of large genomic datasets is the increasing heterogeneity: continuous, binary and discrete features may all be relevant. Coupled with the typically small numbers of training examples, semi-supervised approaches for heterogeneous data are needed; however, current enhancer prediction methods are not designed to handle heterogeneous data in the semi-supervised paradigm.

A Noisy Analog-to-Digital Converter Connects Cytosolic Calcium Bursts to Transcription Factor Nuclear Localization Pulses in Yeast.

Hsu IS, Strome B, Plotnikov S, Moses AM

G3 2019 02 07; 9(2):561-570

PMID: 30573469

Abstract

Several examples of transcription factors that show stochastic, unsynchronized pulses of nuclear localization have been described. Here we show that under constant calcium stress, nuclear localization pulses of the transcription factor Crz1 follow stochastic variations in cytosolic calcium concentration. We find that the size of the stochastic calcium bursts is positively correlated with the number of subsequent Crz1 pulses. Based on our observations, we propose a simple stochastic model of how the signaling pathway converts a constant external calcium concentration into a digital number of Crz1 pulses in the nucleus, due to the time delay from nuclear transport and the stochastic decoherence of individual Crz1 molecule dynamics. We find support for several additional predictions of the model and suggest that stochastic input to nuclear transport may produce noisy digital responses to analog signals in other signaling systems.

Short linear motifs in intrinsically disordered regions modulate HOG signaling capacity.

Strome B, Hsu IS, Li Cheong Man M, Zarin T, Nguyen Ba A, Moses AM

BMC Syst Biol 2018 Jul 03; 12(1):75

PMID: 29970070

Abstract

The effort to characterize intrinsically disordered regions of signaling proteins is rapidly expanding. An important class of disordered interaction modules are ubiquitous and functionally diverse elements known as short linear motifs (SLiMs).