Gene clustering by Latent Semantic Indexing of MEDLINE abstracts
نویسندگان
چکیده
منابع مشابه
Gene clustering by Latent Semantic Indexing of MEDLINE abstracts
MOTIVATION A major challenge in the interpretation of high-throughput genomic data is understanding the functional associations between genes. Previously, several approaches have been described to extract gene relationships from various biological databases using term-matching methods. However, more flexible automated methods are needed to identify functional relationships (both explicit and im...
متن کاملFunctional Cohesion of Gene Sets Determined by Latent Semantic Indexing of PubMed Abstracts
UNLABELLED High-throughput genomic technologies enable researchers to identify genes that are co-regulated with respect to specific experimental conditions. Numerous statistical approaches have been developed to identify differentially expressed genes. Because each approach can produce distinct gene sets, it is difficult for biologists to determine which statistical approach yields biologically...
متن کاملDouble Clustering in Latent Semantic Indexing
Document clustering is a widely researched area of information retrieval. The large amount of documents which must be handled needs automatic organizing. A popular approach to clustering documents and messages is the vector space model, which represents texts with feature vectors, usually generated from the set of terms contained in the message. The clustering based on the document-term frequen...
متن کاملIndexing by Latent Semantic Analysis
A new method for automatic indexing and retrieval is described. The approach is to take advantage of implicit higher-order structure in the association of terms with documents ("semantic structure") in order to improve the detection of relevant documents on the basis of terms found in queries. The particular technique used is singular-value decomposition, in which a large term by document matri...
متن کاملLatent Semantic Indexing
In the previous lecture, we discussed the Singular Value Decomposition (SVD) of the term-document matrix D ∈ <m× n where n is the number of documents in the corpus and m is the number of terms in the vocabulary. With the help of SVD (which is unique up to sign if the singular values are distinct), we can decompose an m×n term-document matrix into three special smaller matrices. The result is fr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bioinformatics
سال: 2004
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/bth464