With the advent of high-throughput biology, we now routinely scan cells and organisms at practically all levels, from genome to protein, metabolism, signaling and other cellular functions. This methodology allowed biological studies to move from a reductionist approach, such as isolation of specific pathways and mechanisms, to a more integrative approach, where biological systems are seen as a ...

With the aim of improving knowledge on the geographical distribution and characterization of malignant tumors in the Autonomous Community of the Basque Country (Spain), age-standardized cancer incidence rates of the 6 most frequent cancer types for patients of each sex between 1986 and 1994 are analyzed, in relation to the towns of the Community. Concretely, we perform a geographical clustering...

introduction raman spectroscopy is a vibrational spectroscopic technique, based on inelastic scattering of monochromatic light. this technique can provide valuable information about biomolecular changes, associated with neoplastic transformation. the purpose of this study was to find raman spectral markers for distinguishing normal samples from cancerous ones in different tissues. materials and...

Lung cancer is worldwide the second death cancer, both in prevalence and lethality, for women men. The applicability of machine learning pattern classification lung detection proposed. Pattern algorithms can classify input data into different classes underlying characteristic features input. Early identification using recognition save lives by analyzing significant number Computed Tomography im...

Introduction As a tumor grows, the demand for oxygen and nutrients increases and it grows further if acquires the ability to induce angiogenesis. In this study, we aimed to present a two-dimensional continuous mathematical model for avascular tumor growth, coupled with a discrete model of angiogenesis. Materials and Methods In the avascular growth model, tumor is considered as a single mass, wh...

We focus on characterizing common and different coexpression patterns among RNAs and proteins in breast cancer tumors. To address this problem, we introduce Joint Random Forest (JRF), a novel nonparametric algorithm to simultaneously estimate multiple coexpression networks by effectively borrowing information across protein and gene expression data. The performance of JRF was evaluated through ...

BACKGROUND Recent advances in high-throughput genotyping have made possible identification of genetic variants associated with increased risk of developing prostate cancer using genome-wide associations studies (GWAS). However, the broader context in which the identified genetic variants operate is poorly understood. Here we present a comprehensive assessment, network, and pathway analysis of t...

We present NDEx 2.0, the latest release of the Network Data Exchange (NDEx) online data commons (www.ndexbio.org) and the ways in which it can be used to (i) improve the quality and abundance of biological networks relevant to the cancer research community; (ii) provide a medium for collaboration involving networks; and (iii) facilitate the review and dissemination of networks. We describe inno...

The study’s primary purpose is to propose an automatic melanoma cancer detection system using the Decision Tree algorithm and convolutional neural network detect compare their accuracy. Group 1 was with a sample size of 10, 2 10. They were iterated 20 times predict accuracy percentage identifying cancer. Compared accuracy(75.58 %), method has substantially higher (85.61%). p=0.018 (p<0.05) I...

Background: The treatment for cancer is often complex, involving many disciplines and therapies, which makes it difficult for Australians living in rural and remote areas to access the full range of care required within their local community. Aim: The Cancer Service Networks National Demonstration Program (CanNET) is a Commonwealth initiative which aimed to improve access to cancer care by link...