Epigenetic Activation of Pro-angiogenic Signaling Pathways in Human Endothelial Progenitors Increases Vasculogenesis.

Human endothelial colony-forming cells (ECFCs) represent a promising source of adult stem cells for vascular repair, yet their regenerative capacity is limited. Here, we set out to understand the molecular mechanism restricting the repair function of ECFCs. We found that key pro-angiogenic pathways are repressed in ECFCs due to the presence of bivalent (H3K27me3/H3K4me3) epigenetic marks, which decreases the cells' regenerative potential.

Learning a cost function for microscope image segmentation.

Quantitative analysis of microscopy images is increasingly important in clinical researchers' efforts to unravel the cellular and molecular determinants of disease, and for pathological analysis of tissue samples. Yet, manual segmentation and measurement of cells or other features in images remains the norm in many fields. We report on a new system that aims for robust and accurate semi-automated analysis of microscope images.

FiloDetect: automatic detection of filopodia from fluorescence microscopy images.

Background: Filopodia are small cellular projections that help cells to move through and sense their environment. Filopodia play crucial roles in processes such as development and wound-healing. Also, increases in filopodia number or size are characteristic of many invasive cancers and are correlated with increased rates of metastasis in mouse experiments.

Object detection with DoG scale-space: a multiple kernel learning approach.

Difference of Gaussians (DoG) scale-space for an image is a significant way to generate features for object detection and classification. While applying DoG scale-space features for object detection/classification, we face two inevitable issues: dealing with high dimensional data and selecting/weighting of proper scales. The scale selection process is mostly ad-hoc to date.

A districted neural network for start codon prediction.

Following the theory on regional and national voting, we constructed a regional voting version NN from Pedersen-Nielsen's NN for start codon prediction in nucleotide sequences. Experiments on the TIS data of vertebrate and Arabidopsis thaliana sequences showed improved performances (Matthews correlation coefficients) of 7% and 14% over the original NN.

Airway segmentation and measurement in CT images.

In this paper we describe a methodology for constructing the airways from Cone Beam CT data and representing changes before and after a medical procedure. A seed region is automatically detected for the first CT slice using a heuristic algorithm incorporating morphological filtering. Our approach then extracts relevant contours on 3D slices by using gradient vector flow (GVF) snakes, modified by an edge detection and snake-shifting step.