RODRIGO AKIRA WATANABE
Projetos de Pesquisa
Unidades Organizacionais
P ICHC, Hospital das Clínicas, Faculdade de Medicina - Médico
LIM/15 - Laboratório de Investigação em Neurologia, Hospital das Clínicas, Faculdade de Medicina
LIM/15 - Laboratório de Investigação em Neurologia, Hospital das Clínicas, Faculdade de Medicina
2 resultados
Resultados de Busca
Agora exibindo 1 - 2 de 2
- CoGA: An R Package to Identify Differentially Co-Expressed Gene Sets by Analyzing the Graph Spectra(2015) SANTOS, Suzana de Siqueira; GALATRO, Thais Fernanda de Almeida; WATANABE, Rodrigo Akira; OBA-SHINJO, Sueli Mieko; MARIE, Suely Kazue Nagahashi; FUJITA, AndreGene set analysis aims to identify predefined sets of functionally related genes that are differentially expressed between two conditions. Although gene set analysis has been very successful, by incorporating biological knowledge about the gene sets and enhancing statistical power over gene-by-gene analyses, it does not take into account the correlation (association) structure among the genes. In this work, we present CoGA (Co-expression Graph Analyzer), an R package for the identification of groups of differentially associated genes between two phenotypes. The analysis is based on concepts of Information Theory applied to the spectral distributions of the gene co-expression graphs, such as the spectral entropy to measure the randomness of a graph structure and the Jensen-Shannon divergence to discriminate classes of graphs. The package also includes common measures to compare gene co-expression networks in terms of their structural properties, such as centrality, degree distribution, shortest path length, and clustering coefficient. Besides the structural analyses, CoGA also includes graphical interfaces for visual inspection of the networks, ranking of genes according to their ""importance"" in the network, and the standard differential expression analysis. We show by both simulation experiments and analyses of real data that the statistical tests performed by CoGA indeed control the rate of false positives and is able to identify differentially co-expressed genes that other methods failed.
- Adhesive Leaf Created by a Corona Discharge(2018) LEE, Wonseok; SON, Jongsang; KIM, Seonghyun; YANG, Dongmin; CHOI, Seungyeop; WATANABE, Rodrigo Akira; HWANG, Kyo Seon; LEE, Sang Woo; LEE, Gyudo; YOON, Dae SungHere, we report a new concept of both the adhesive manner and material, named ""adhesive leaf (AL),"" based on the leaf of the plant Heteropanax fragrans. The treatment of the corona discharge on the leaf surface can cause the nano-/microdestruction of the leaf epidermis, resulting in an outward release of sap. The glucose-containing sap provided the AL with a unique ability to stick to various substrates such as steel, polypropylene, and glass. Moreover, we reveal that the AL adhesion strength depends on the AL size, as well as the corona-discharge intensity. Conventional adhesives, such as glue and bond, lose their adhesive property and leave dirty residues upon the removal of the attached material. Unlike the conventional methods, the AL is advantageous as it can be repeatedly attached and detached thoroughly until the sap liquid is exhausted; its adhesive ability is maintained for at least three weeks at room temperature. Our findings shed light on a new concept of a biodegradable adhesive material that is created by a simple surface treatment.