Cells govern biological functions through complex biological networks. Perturbations to networks may drive cells to new phenotypic states, for example, tumorigenesis. Identifying how genetic lesions perturb molecular networks is a fundamental challenge. This study used large-scale human interactome data to systematically explore the relationship among network topology, somatic mutation, evoluti...

Knowledge gaps persist about the efficacy of cancer prevention strategies based on dietary food components. Adaptations to nutrient supply are executed through tuning of multiple protein networks that include transcription factors, histones, modifying enzymes, translation factors, membrane and nuclear receptors, and secreted proteins. However, the simultaneous quantitative and qualitative measu...

In a tumor cell, the development of acquired therapeutic resistance and the ability to survive in extracellular environments that differ from the primary site are the result of molecular adaptations in potentially highly plastic molecular networks. The accurate prediction of intracellular networks in a tumor remains a difficult problem in cancer informatics. In order to make truly rational pati...

Skin cancer is a major public health problem, with over 5 million newly diagnosed cases in the United States each year. Melanoma is the deadliest form of skin cancer, responsible for over 9,000 deaths each year. In this paper, we propose an ensemble of deep convolutional neural networks to classify dermoscopy images into three classes. To achieve the highest classification accuracy, we fuse the...

in recent years mobile networks have expanded dramatically, compared with other wireless networks. routing protocols in these networks are designed with the assumption that there is no attacker node, so routing protocols are vulnerable to various attacks in these networks. in this paper, we review the network layer attacks and then we simulate the impact of black hole attack on ad hoc on demand...

INTRODUCTION: Although accurate segmentation of the prostatic subregions is a crucial step for prostate cancer diagnosis, it remains challenge. OBJECTIVES: To propose deep learning (DL)-based cropping pipeline to improve performance DL networks segmenting prostate’s periphe

Advances in the generation and interpretation of proteomics data have spurred a transition from focussing on protein identification to functional analysis. Here, we review recent proteomics results that have elucidated new aspects of the role and regulation of signal transduction pathways in cancer using the epidermal growth factor receptor (EGFR), ERK and breakpoint cluster region (BCR)–ABL1 n...

Prognostic genes are key molecules informative for cancer prognosis and treatment. Previous studies have focused on the properties of individual prognostic genes, but have lacked a global view of their system-level properties. Here we examined their properties in gene co-expression networks for four cancer types using data from 'The Cancer Genome Atlas'. We found that prognostic mRNA genes tend...