26 papers · ranked by Valyu relevance
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…
Mohsen Hajiloo, Hamid R Rabiee, Mahdi Anooshahpour
Background The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and…
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…
Thanh Nguyen, Abbas Khosravi, Douglas Creighton, Saeid Nahavandi + 1 more
'Enrique Hernandez-Lemus'] This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five…
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…
R Simon
DNA microarrays are a potentially powerful technology for improving diagnostic classification, treatment selection and therapeutics development. There are, however, many potential pitfalls in the use of microarrays that result in false leads and erroneous conclusions. This paper provides a review of the key features to…
Jaison Bennet, Chilambuchelvan Arul Ganaprakasam, Kannan Arputharaj
Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in…
Mrutyunjaya Panda
Gene is the basic unit of storage containing hereditary information in living beings. For the technical point of view,it can be treated as a distinct sequence of nucleotides constituting part of a chromosome. Microarrays data analysis is relatively a new technology that aims to help in finding the right treatment for…
Min Xu, Rudy Setiono
Various approaches to gene selection for cancer classification based on microarray data can be found in the literature and they may be grouped into two categories: univariate methods and multivariate methods. Univariate methods look at each gene in the data in isolation from others. They measure the contribution of a…
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…
Khalid Raza
Microarray is one of the essential technologies used by the biologist to measure genome-wide expression levels of genes in a particular organism under some particular conditions or stimuli. As microarrays technologies have become more prevalent, the challenges of analyzing these data for getting better insight about…
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…
Xiaohui Yang, Li Tian, Yunmei Chen, Lijun Yang + 2 more
'Wenming Wu'] Abstract—Sparse representation based classification (SRC) methods have achieved remarkable results. SRC, however, still suffer from requiring enough training samples, insufficient use of test samples and instability of representation. In this paper, a stable inverse projection representation based…
Jard H. de Vries, Daniel Kling, Athina Vidaki, Pascal Arp + 6 more
Single nucleotide polymorphism (SNP) data generated with microarray technologies have been used to solve murder cases via investigative leads obtained from identifying relatives of the unknown perpetrator included in accessible genomic databases, referred to as investigative genetic genealogy (IGG). However, SNP…
Alina Frolova, Vladyslav Bondarenko, Maria Obolenska
According to major public repositories statistics an overwhelming majority of the existing and newly uploaded data originates from microarray experiments. Unfortunately, the potential of this data to bring new insights is limited by the effects of individual study-specific biases due to small number of biological…
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…
Ernur Saka, Benjamin J. Harrison, Kirk West, Jeffrey C. Petruska + 1 more
Since the introduction of microarrays in 1995, researchers world-wide have used both commercial and custom-designed microarrays for understanding differential expression of transcribed genes. Public databases such as ArrayExpress and the Gene Expression Omnibus (GEO) have made millions of samples readily available. One…
Majid Mohammadi, Hossein Sharifi Noghabi, Ghosheh Abed Hodtani, Habib Rajabi Mashhadi
One of the central challenges in cancer research is identifying significant genes among thousands of others on a microarray. Since preventing outbreak and progression of cancer is the ultimate goal in bioinformatics and computational biology, detection of genes that are most involved is vital and crucial. In this…
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…
Kazi Ferdous Mahin, Md. Robiuddin, Mujahidul Islam, Shayed Ashraf + 2 more
Cancer is one of the major causes of human death per year. In recent years, cancer identification and classification using machine learning have gained momentum due to the availability of high throughput sequencing data. Using RNA-seq, cancer research is blooming day by day and new insights of cancer and related…
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…
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…
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…
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…
Authors not listed
Large-scale de novo nucleic acid synthesis is a powerful tool enabling researchers to better understand and engineer biological systems. Fields ranging from genomics to nucleic acid therapeutics to synthetic biology make use of high-throughput experimental approaches requiring access to large pools or libraries of DNA…