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A Microarray Analysis Technique Using a Self-Organizing Multiagent Approach
2021Microarray technology is fully established among the research fields in genetic domain. Academia and industrial researchers investigate and analyze genes' expression to obtain more and more useful information about given organisms, with the aim to perform better disease diagnosis and prediction, accurate medical data analysis, etc.
Forestiero A +3 more
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A colon cancer microarray analysis technique
2017 E-Health and Bioengineering Conference (EHB), 2017Colon cancer is a very spread malady at international level, symptoms occurring due to a number of vary conditions that may be totally ignored in early stages. Moreover, even treated surgical or with chemotherapy, lots of patients occur recurrence at a specific period of time, so more validated findings in the microarray analysis field, should improve ...
Irina-Oana Petre, Catalin Buiu
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A novel tissue array technique for high-throughput tissue microarray analysis — microarray groups
In Vitro Cellular & Developmental Biology - Animal, 2007Tissue microarrays are ordered arrays of hundreds to thousands of tissue cores in a single paraffin block. We invented a novel method to make a high-throughput microarray group. Conventional smaller tissue microarrays were made first and then sectioned.
Hui-Yong, Jiang +4 more
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Single Nucleotide Polymorphism Analysis in HIV and Kaposi's Sarcoma Disease by Microarray Technique
Current HIV Research, 2020Background: Emergence of Kaposi's Sarcoma in the cases other than HIV, following the use of immunosuppressant drugs, demonstrates that it is related to weak immunity. The fact that this malignancy does not occur in every HIV-positive patient suggests that genetic predisposition may also be effective.
Ismail Koyuncu +6 more
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A study on microarray image gridding techniques for DNA analysis
2014 2nd International Conference on Electronic Design (ICED), 2014Microarray is one of the most promising tools available for researchers in the life sciences to study gene expression profiles. Through microarray analysis, gene expression levels can be obtained, and the biological information of a disease can be identified. The gene expression information embedded in the microarray is extracted using image-processing
Maziidah Mukhtar Ahmad +2 more
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J. Comput. Biol., 2019
The employment of machine learning (ML) approaches to extract gene expression information from microarray studies has increased in the past years, specially on cancer-related works.
B. C. Feltes +3 more
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The employment of machine learning (ML) approaches to extract gene expression information from microarray studies has increased in the past years, specially on cancer-related works.
B. C. Feltes +3 more
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Optical genome mapping for structural variation analysis in hematologic malignancies
American journal of hematology/oncology, 2022Optical genome mapping (OGM) is a technology that is rapidly being adopted in clinical genetics laboratories for its ability to detect structural variation (e.g., translocations, inversions, deletions, duplications, etc.) and replace several concurrent ...
Adam C. Smith +2 more
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Clustering Techniques from Significance Analysis of Microarrays
2015Microarray technology is a prominent tool that analyzes many thousands of gene expressions in a single experiment as well as to realize the primary genetic causes of various human diseases. There are abundant applications of this technology and its dataset is of high dimension and it is difficult to analyze the whole gene sets.
K. Nirmalakumari +2 more
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Spectral Estimation Techniques for DNA Sequence and Microarray Data Analysis
Current Bioinformatics, 2007Spectral estimation techniques are widely used in modern signal processing systems. Recently, they have found important applications to the analysis of DNA data. In this paper, we review parametric and non-parametric spectral estimation methods for DNA sequence and microarray data analysis. The discrete Fourier transform (DFT) is the most commonly used
Yan, Hong, Pham, Tuan D.
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2020 IEEE 5th International Conference on Computing Communication and Automation (ICCCA), 2020
Clustering is a very useful machine learning technique to find the underlying classification of unlabeled data. In computational biology, clustering techniques are extensively used to identify a group of biomolecules responsible for biological activity in animals.
Prasad Bandyopadhyay +2 more
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Clustering is a very useful machine learning technique to find the underlying classification of unlabeled data. In computational biology, clustering techniques are extensively used to identify a group of biomolecules responsible for biological activity in animals.
Prasad Bandyopadhyay +2 more
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