Abstract:
A regioselectively lateral nanowire growth process is provided to improve integration degree of device by selecting desired location when nano device is manufactured and growing nanowire. A regioselectively lateral nanowire growth process comprises steps of: forming the first oxide silicon thin film on a silicon substrate; forming two or more long grooves; removing the remaining first oxide silicon thin film; forming a silicon core surrounded by the second oxide silicon thin film(3); etching perpendicularly a predetermined part of both sides of a silicon core surrounded by the second silicon thin film by patterning and removing it; forming a hollow channel of which the both sides are opened; depositing a catalyst metal layer on one end of the hollow channel; forming a protective film on a top surface of the catalyst metal layer; and growing nanowire in the hollow channel from the catalyst metal layer(7) to the silicon substrate in horizontal direction.
Abstract:
마이크로어레이 데이터 분석 시스템은 복수의 처리 중 i번째 처리에 대한 복수의 반복 중에서 j번째 반복에 포함된 복수의 유전자의 강도로 i번째 처리의 j번째 반복에 대한 표준 벡터를 생성하고, 복수의 i와 복수의 j에 대해서 복수의 표준 벡터를 생성한다. 그리고 시스템은 복수의 표준 벡터 중에서 두 표준 벡터 사이의 상관 계수를 계산하고, 상관 계수로 마이크로어레이 데이터의 품질 및 재현성을 분석한다. 마이크로어레이, 재현성, 품질, 상관, 콜모고로프-스미르노프, 검증
Abstract:
A method and a system for analyzing microarray data are provided to analyze quality of the microarray data objectively which is generated from a plurality of treatments by using a chip correlation coefficient according to the same or different treatment. A correlation module(10) generates a plurality of reference vectors according to treatments and treatment repetitions, generates the reference vector for m-th repetition of n-th treatment by using intensity of a plurality of genes included in the m-th repetition of the n-th treatment, and calculates a correlation coefficient between two reference vectors among a plurality of reference vectors. An analyzing module(20) analyzes microarray data by using the correlation coefficient. The analyzing module compares the quality of the first and second treatments by comparing the correlation coefficient of a correlation group in the repeated treatments of the first treatment with the correlation coefficient of the correlation group in the repeated treatments of the second treatment.