24 papers · ranked by Valyu relevance
Jingeun Kim, Yourim Yoon, Hye-Jin Park, Yong-Hyuk Kim + 1 more
Microarrays are applications of electrical engineering and technology in biology that allow simultaneous measurement of expression of numerous genes, and they can be used to analyze specific diseases. This study undertakes classification analyses of various microarrays to compare the performances of classification…
Nikita Bhandari, Rahee Walambe, Ketan Kotecha, Satyajeet P. Khare
Computational analysis methods including machine learning have a significant impact in the fields of genomics and medicine. High-throughput gene expression analysis methods such as microarray technology and RNA sequencing produce enormous amounts of data. Traditionally, statistical methods are used for comparative…
Aayush Adhikari, Sandesh Bhatta, Harendra S. Jangwan, Amit Mishra + 5 more
High dimensionality in datasets produced by microarray technology presents a challenge for Machine Learning (ML) algorithms, particularly in terms of dimensionality reduction and handling imbalanced sample sizes. To mitigate the explained problems, we have proposed hybrid ensemble feature selection techniques with…
Maryam Eshraghi Evari, Md. Nasir Sulaiman, Amir Behjat
Data Authors: ['Maryam Eshraghi Evari' 'Md. Nasir Sulaiman' 'Amir Behjat'] DNA microarray gene-expression data has been widely used to identify cancerous gene signatures. Microarray can increase the accuracy of cancer diagnosis and prognosis. However, analyzing the large amount of gene expression data from microarray…
Atikul Islam, Tapas Bhadra, Kalyani Mali, Jayant Giri + 3 more
This article basically explores the impact of univariate & multivariate filter-based feature selection methodologies on enhancing the classification performance for the real-life classification problems. Our study considers two univariate filter-based feature selection techniques, namely, Chi-square and Fisher score…
Rajul Mahto, Saboor Uddin Ahmed, Rizwan ur Rahman, Rabia Musheer Aziz + 4 more
'Rabia Musheer Aziz' 'Priyanka Roy' 'Saurav Mallik' 'Aimin Li' 'Mohd Asif Shah'] Cancer prediction in the early stage is a topic of major interest in medicine since it allows accurate and efficient actions for successful medical treatments of cancer. Mostly cancer datasets contain various gene expression levels as…
Emine Akpinar, Batuhan Hangun, Murat Oduncuoglu, Oguz Altun + 2 more
'Onder Eyecioglu' 'Zeynel Yalcin'] Abstract—DNA microarray technology enables the simultaneous measurement of expression levels of thousands of genes, thereby facilitating the understanding of the molecular mechanisms underlying complex diseases such as brain tumors and the identification of diagnostic genetic…
Ajin R. Nair, Harikumar Rajaguru, M. S. Karthika, C. Keerthivasan
The microarray gene expression data poses a tremendous challenge due to their curse of dimensionality problem. The sheer volume of features far surpasses available samples, leading to overfitting and reduced classification accuracy. Thus the dimensionality of microarray gene expression data must be reduced with…
Karthika M S, Harikumar Rajaguru, Ajin R. Nair, Antonio Brunetti
Microarray gene expression-based detection and classification of medical conditions have been prominent in research studies over the past few decades. However, extracting relevant data from the high-volume microarray gene expression with inherent nonlinearity and inseparable noise components raises significant…
Fadi Alharbi, Aleksandar Vakanski
Cancer is a term that denotes a group of diseases caused by abnormal growth of cells that can spread in different parts of the body. According to the World Health Organization (WHO), cancer is the second major cause of death after cardiovascular diseases. Gene expression can play a fundamental role in the early…
Giuseppe Agapito, Marianna Milano, Mario Cannataro, Quan Zou
Gene expression and SNPs data hold great potential for a new understanding of disease prognosis, drug sensitivity, and toxicity evaluations. Cluster analysis is used to analyze data that do not contain any specific subgroups. The goal is to use the data itself to recognize meaningful and informative subgroups. In…
Fei Deng, Catherine H. Feng, Nan Gao, Lanjing Zhang
Normalization is a critical step in quantitative analyses of biological processes. Recent works show that cross-platform integration and normalization enable machine learning (ML) training on RNA microarray and RNA-seq data, but no independent datasets were used in their studies. Therefore, it is unclear how to improve…
Samuel Bharti, Nikita Krishnan, Arian Veyssi, Maryam Momeni + 1 more
Microarray data enables biologists to extract differentially expressed genes (DEGs) across multiple phenotypes. While several pipelines and tools exist to perform microarray data analysis, they are targeted to users with moderate to advanced computational understanding and lack an easy-to-use, interactive and dynamic…
Luca Visentin, Luca Munaron, Federico Alessandro Ruffinatti
Tens of thousands of gene expression data sets describing a variety of model organisms in a many different pathophysiological conditions are currently stored in publicly available databases such as Gene Expression Omnibus (GEO) and ArrayExpress. As microarray technology is giving way to RNA-Seq, it becomes strategic to…
Christina Bligaard Pedersen, Benito Campos, Neeraja M. Krishnan, Binay Panda + 4 more
Molecular subtyping is essential to infer tumor aggressiveness and predict prognosis. In practice, tumor profiling requires in-depth knowledge of bioinformatics tools involved in the processing and analysis of the generated data. Additionally, data incompatibility (e.g., microarray vs. RNA sequencing data) and…
Keegan Flanagan, Steven Pelech, Yossef Av-Gay, Khanh Dao Duc
Analysis of signal transduction pathways relies on monitoring global changes in cellular response to perturbation or genetic manipulation. Antibody microarray data provides an increasingly viable tool for the monitoring and analyzing high throughput expression and protein phosphorylation data. However, computational…
Preston Raab, W. Evan Johnson, Stephen R. Piccolo
Precision medicine relies on accurate and generalizable predictions for patients across the spectrum of human diversity. Because capturing biological heterogeneity requires large sample sizes, researchers must often aggregate data from several experimental batches or independent studies. This integration allows for…
Chin Hong Ooi, Nam-Trung Nguyen, Gregor Kijanka
Protein arrays are systematically arranged, large collections of annotated proteins on planar surfaces commonly used for the characterisation of protein binding events against a wide range of possible probes. These may include analyses of protein-protein, peptide-protein, enzyme-substrate or antibody-antigen…
Sunil Kumar Prabhakar, Semin Ryu, In cheol Jeong, Dong-Ok Won
One of the major reasons of mortality in human beings is cancer, and there is an absolute necessity for doctors to identify and treat a person suffering from it. Leukemia is a group of blood cancers that usually originates in the bone marrow and results in very high number of abnormal cells. For the diagnosis of…
Aarav Arora, Igor Tsigelny, Valentina Kouznetsova
Purpose Laryngeal cancer (LC) is the most common head and neck cancer, which often goes undiagnosed due to the expensiveness and inaccessible nature of current diagnosis methods. Many recent studies have shown that microRNAs (miRNAs) are crucial biomarkers for a variety of cancers. Methods In this study, we create a…
Authors not listed
Terminally labeled DNA oligonucleotides have wide applications in modern biology and biotechnological applications. It has been observed that the fluorescent intensity of light released from these fluorescent labels is heavily influenced by the terminal sequence of nucleotides. Recent studies have assayed and published…
Anahita Banaei, Shadrokh Samavi, Ebrahim Nasr Esfahani
Microarray technology is a new and powerful tool for the concurrent monitoring of a large number of gene expressions. Each microarray experiment produces hundreds of images. Each digital image requires a large storage space. Hence, real-time processing of these images and transmission of them necessitates efficient and…
Authors not listed
Microarrays are widely used for detecting target analytes and biomarkers, with fabrication methods ranging from non-contact to contact bioprinting techniques. Microcontact bioprinting (μCP), which utilizes elastomeric stamps to transfer biorecognition molecules (bioinks) onto substrates, offers advantages such as…
Shadman Khan, Amid Shakeri, Jonathan Monteiro, Simrun Tariq + 5 more
With both foodborne illness and food spoilage detrimentally impacting human health and the economy, there is growing interest in the development of in situ sensors that offer real-time monitoring of food quality within enclosed food packages. While oligonucleotide-based fluorescent sensors have illustrated significant…