Mühendislik Fakültesi / Faculty of Engineering
Permanent URI for this collectionhttps://hdl.handle.net/11727/1401
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Item Inferring Similarity between Time-Series Microarrays: A Content-based Approach(2015) Sener, Duygu Dede; Ogul, Hasan; 0000-0001-6766-4977Public repositories for gene expression studies have been growing rapidly in the last decade. Retrieval of gene expression experiments based on textual descriptions does not provide sufficient data for biologists and clinicians. Content-based search has recently become more desirable in retrieving similar experiments. Current methods for content-based retrieval cannot address the problem of profiling the gene behaviors in multiple measurement points, i.e. in time course. This study, to the best of our knowledge, is the first attempt to build a fingerprint for each gene by considering all time points to infer its time-course profile to represent the experiment content in an information retrieval framework. An empirical study is performed on a large dataset of Arabidopsis microarrays from Gene Expression Omnibus (GEO). Experimental results show that relevant experiments are retrieved based on content similarity.Item Inferring Microarray Relevance By Enrichment Of Chemotherapy Resistance-Based MicroRNA Sets(2015) Acici, Koray; Ogul, Hasan; 0000-0002-3821-6419; HDM-9910-2022Inferring relevance between microarray experiments stored in a gene expression repository is a helpful practice for biological data mining and information retrieval studies. In this study, we propose a knowledge-based approach for representing microarray experiment content to be used in such studies. The representation scheme is specifically designed for inferring a disease-associated relevance of microRNA experiments. A group of annotated microRNA sets based on their chemotherapy resistance are used for a statistical enrichment analysis over observed expression data. A query experiment is then represented by a single dimensional vector of these enrichment statistics, instead of raw expression data. According to the results, new representation scheme can provide a better retrieval performance than traditional differential expression-based representation.Item Comparison of Similarity Metrics in Microarray Experiment Retrieval(2015) Acici, Koray; Ogul, Hasan; 0000-0002-3821-6419; HDM-9910-2022Content-based retrieval of biological experiments is a recent challenge in bioinformatics. The task is to search in a database using a query-by-example without any meta-data annotation. In this study, for retrieving relevant microRNA experiments from microarray repositories, performance evaluation of known similarity metrics was conducted to compare experiment fingerprints. It was shown that Spearman correlation coefficient outperformed others by comparison on real datasets. This result shows that ranks of fingerprint values are more important than the exact values in experiment fingerprint.Item Information Retrieval in Metal Music Sub Genres(2017) Acici, Koray; Asuroglu, Tunc; Ogul, Hasan; 0000-0003-4153-0764; HDM-9910-2022; AAC-7834-2020Digital music platforms use meta-data based information retrieval systems for offering songs to users for their own taste of music. According to this system, songs that are labeled by other users are compared to songs that user listened and similar labeled songs are retrived in the process. In this situtation, information retrieval is independent from song content and subjective. To achieve objectivity, content based information retrieval systems are needed. In this study, a content-based music retrieval system based on one dimensional local binary pattern features which are extracted from audio data is proposed. Instead of retrieving different music genres, retrieval is applied on metal music sub-genres which have not been studied before and results are reported.