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公开(公告)号：KR1020130102395A
公开(公告)日：2013-09-17
申请号：KR1020120023595
申请日：2012-03-07
Applicant: 한국과학기술원
Abstract: PURPOSE: A domain prediction device, a method, and a computer-readable recording medium for recording a program for performing thereof in a computer are provided to predict a domain, based on physico-chemical properties of an amino acid sequence and a secondary structure of a protein, which is difficult to predict with a method for comparing only similarities between sequences. CONSTITUTION: A domain prediction device, a method, and a computer-readable recording medium for recording a program for performing thereof in a computer comprise the following steps: a database (100) stores sequential information of a domain, physico-chemical property information of an amino acid sequence, and secondary structure information; a sequence feature detecting part (200) extracts a sequence feature about the sequential information by using the sequential information, the physico-chemical property information, and the secondary structure information; a machine learning part (300) machine-learns a sequence feature; a sequence analysis part (400) extracts a candidate sequence from inputted protein sequential information; and the sequence analysis part predicts a domain corresponding to the candidate sequence by using a sequence feature of the domain which is machine-learned from the machine learning part. [Reference numerals] (100) Database; (110) Domain DB; (120) Physicochemical feature DB; (130) Secondary structure DB; (200) Sequence feature detecting part; (210) Physicochemical feature generating unit; (220) Secondary structure generating unit; (230) Sequence feature combination unit; (300) Machine learning part; (310) Separating unit; (320) Training unit; (330) Importance determining unit; (400) Sequence analysis part; (410) Input unit; (420) Candidate sequence extracting unit; (430) Domain prediction unit; (440) Output unit
Abstract translation: 目的：提供一种用于在计算机中记录用于执行程序的域预测装置，方法和计算机可读记录介质，用于基于氨基酸序列和二级结构的物理化学性质来预测域 一种蛋白质，难以用仅用于比较序列之间相似性的方法来预测。 构成：用于记录在计算机中执行的程序的域预测装置，方法和计算机可读记录介质包括以下步骤：数据库（100）存储域的顺序信息，物理化学属性信息 氨基酸序列和二级结构信息; 序列特征检测部分（200）通过使用顺序信息，物理化学性质信息和二级结构信息来提取关于顺序信息的序列特征; 机器学习部分（300）机器 - 学习序列特征; 序列分析部分（400）从输入的蛋白质序列信息中提取候选序列; 并且序列分析部分通过使用从机器学习部分机器学习的域的序列特征来预测与候选序列相对应的域。 （附图标记）（100）数据库; （110）域DB; （120）物理化学特征DB; （130）二次结构DB; （200）序列特征检测部分; （210）物理化学特征生成单元; （220）二次结构生成单元; （230）序列特征组合单位; （300）机器学习部分; （310）分离单元; （320）培训单位; （330）重要性确定单元; （400）序列分析部分; （410）输入单元; （420）候选序列提取单元; （430）域预测单元; （440）输出单元
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Patent Agency Ranking2.发明授权
公开(公告)号：KR100920782B1
公开(公告)日：2009-10-08
申请号：KR1020080100233
申请日：2008-10-13
Applicant: 한국과학기술원
Abstract: PURPOSE: A system and method for the prediction of Type-II Polyketide Synthases and their Polyketide based on microbial genome analysis are provided to predict synthesized polyketide by analyzing gene cluster. CONSTITUTION: A system and method for the prediction of Type-II Polyketide Synthases and their Polyketide based on microbial genome analysis includes the input output manager, the PKS database, the machine learning classifier, the machine learning training part, the order analysis part, the gene cluster analysis part, and the heredity sieve analysis part. The input output manager(100) receives gene ranking files for the type 2 PKS and polyketide. The PKS database(200) saves a polyketide, and the type-2 PKS and type-2 PKS domain ranking information. The machine learning classifier(400) is comprised of the machine learner more than one. The machine learning training part(300) trains the machine learner of the machine learning classifier.
Abstract translation: 目的：提供基于微生物基因组分析预测II型聚酮化合物及其聚酮化合物的系统和方法，通过分析基因簇来预测合成的聚酮化合物。 构成：基于微生物基因组分析预测II型聚酮化合物及其聚酮化合物的系统和方法，包括输入输出管理者，PKS数据库，机器学习分类器，机器学习训练部分，定单分析部分， 基因簇分析部分，遗传筛分析部分。 输入输出管理器（100）接收2型PKS和聚酮化合物的基因排序文件。 PKS数据库（200）保存聚酮化合物，以及2型PKS和2型PKS结构域的排序信息。 机器学习分类器（400）由机器学习者多于一个组成。 机器学习训练部分（300）训练机器学习分类器的机器学习者。
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公开(公告)号：KR101373254B1
公开(公告)日：2014-03-13
申请号：KR1020120023595
申请日：2012-03-07
Applicant: 한국과학기술원
Abstract: 본 발명의 한 실시예에 따른 도메인 예측 장치는 도메인의 서열 정보, 아미노산 서열의 물리화학적 특징 정보 및 이차 구조 정보 중 적어도 하나를 저장하는 데이터베이스, 서열 정보, 상기 물리화학적 특징 정보 및 상기 이차 구조 정보를 이용하여 상기 서열 정보에 대한 서열 특징을 추출하는 서열 특징 추출부, 상기 서열 특징을 기계 학습하는 기계 학습부, 그리고 입력된 단백질의 서열 정보로부터 후보 서열을 추출하고, 상기 서열 특징 추출부에 의하여 추출된 상기 후보 서열의 서열 특징 및 상기 기계 학습부에서 기계 학습된 상기 도메인의 서열 특징을 이용하여 상기 후보 서열에 대응하는 도메인을 예측하는 서열 분석부를 포함한다.
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公开(公告)号：KR100705759B1
公开(公告)日：2007-04-10
申请号：KR1020050004320
申请日：2005-01-17
Applicant: 한국과학기술원
IPC: G02B6/02
Abstract: 본 발명은 직접 광패터닝에 의한 평판형 멀티모드 광도파로 제조방법에 관한 것으로 보다 상세하게는 굴절율의 조정이 가능하고, 다른 유전 영역 사이에서 매끄러운 굴절률 분포를 갖는 광도파로를 클래드층의 형성과정과 코어층의 식각과정이 불필요하여 공정을 단순화는 광도파로용 재료 및 제조방법에 관한 것이다.
본 발명은 광조사에 의하여 굴절률 또는 부피가 변화되는 광민감성 하이브리드재료를 10 마이크론 이상 두께로 코팅하는 단계와, 코팅된 광도파로의 소정영역에 광을 조사하여 광조사부위의 굴절률 변화로 인한 직접 멀티모드 광도파로를 형성하는 단계를 포함함을 특징으로 한다.
본 발명에 의하면 별도로 광도파로의 클래드층의 형성과정과 코어층의 식각 공정이 불필요하여 공정을 단축할 수 있을 뿐만 아니라, 광특성 및 안정성이 우수한 재료로 광손실이 적으면서 10 마이크론 이상 크기의 구조를 갖는 멀티모드 광도파로를 제조할 수 있게 된다.-
公开(公告)号：KR1020060084057A
公开(公告)日：2006-07-21
申请号：KR1020050004320
申请日：2005-01-17
Applicant: 한국과학기술원
IPC: G02B6/02
CPC classification number: G02B6/24 , G02B6/138 , B05D3/067 , G02B2006/12035
Abstract: Disclosed is a method of producing a planar multimode optical waveguide by direct photo-patterning and, more particularly, to an optical waveguide material and a method of producing the same. It is possible to control the refractive index of the optical waveguide, and the optical waveguide has a desirable refractive index distribution throughout different dielectric regions. In the method, it is unnecessary to conduct processes of forming a clad layer and of etching a core layer, thus a production process is simplified. The method comprises coating a photosensitive hybrid material having a refractive index or a volume changed by light radiation, in a thickness of 10 microns or more, and radiating light having a predetermined wavelength onto the coated photosensitive hybrid material to form the multimode optical waveguide due to a change in refractive index of a portion onto which light is radiated.
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公开(公告)号：KR101213701B1
公开(公告)日：2012-12-18
申请号：KR1020110141765
申请日：2011-12-23
Applicant: 한국과학기술원
CPC classification number: G06F19/26
Abstract: PURPOSE: A bio-signal transmission control circuit searching system and method thereof are provided to offer bio-signal control circuit information by systemically storing and arranging the bio-signal control circuit information. CONSTITUTION: An input and output management unit(100) outputs an analysis result by receiving a bio-signal transmission network file from a user. A control circuit database(200) stores a graph which includes the same phase as a bio signal control circuit. A control circuit graph creation unit(300) creates a phase graph having the same phase as a graph of the bio-signal control circuit by using an equivalent phase graph creation unit. A searching path searching unit(400) determines a searching path by constructing a searching path tree from the graph. A control circuit searching unit(500) finds the bio-signal control circuit by using a control circuit searching unit which uses the searching path searching unit. [Reference numerals] (100) Input and output management unit; (200) Control circuit database; (300) Control circuit graph creation unit; (310) In-phase-graph creation apparatus; (400) Searching path searching unit; (410) Searching path tree construction apparatus; (420) Searching path discriminator; (500) Control circuit searching unit; (510) Control circuit searching apparatus; (600) Bio-signal front-end network analysis unit; (610) Graph extraction apparatus; (620) Proximity node classification apparatus; (630) Control circuit analysis apparatus; (AA) User
Abstract translation: 目的：提供生物信号传输控制电路搜索系统及其方法，通过系统地存储和布置生物信号控制电路信息来提供生物信号控制电路信息。 构成：输入和输出管理单元（100）通过从用户接收生物信号传输网络文件来输出分析结果。 控制电路数据库（200）存储包括与生物信号控制电路相同的相位的曲线图。 控制电路图创建单元（300）通过使用等效相位图创建单元创建与生物信号控制电路的曲线图相同相位的相位图。 搜索路径搜索单元（400）通过从图形构造搜索路径树来确定搜索路径。 控制电路搜索单元（500）通过使用使用搜索路径搜索单元的控制电路搜索单元来找到生物信号控制电路。 （附图标记）（100）输入输出管理单元; （200）控制电路数据库; （300）控制电路图创建单元; （310）同相图生成装置; （400）搜索路径搜索单元; （410）搜索路径树施工装置; （420）搜索路径鉴别器; （500）控制电路搜索单元; （510）控制电路检索装置; （600）生物信号前端网络分析单元; （610）图形提取装置; （620）接近节点分类装置; （630）控制电路分析装置; （AA）用户
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