Results 31 to 40 of about 557,537 (198)

CIDA: An integrated software for the design, characterisation and global comparison of microarrays

Journal of Integrative Bioinformatics, 2007
Microarray technology has had a significant impact in the field of systems biology involving the investigation into the biological systems that regulate human life. Identifying genes of significant interest within any given disease on an individual basis
Khalid Sabah, Khan Mohsin, Symonds Alistair, Fraser Karl, Wang Ping, Liu Xiaohui, Li Suling   +6 more
doaj   +1 more source

A Novel Ensemble Feature Selection Technique for Cancer Classification Using Logarithmic Rank Aggregation Method

Düzce Üniversitesi Bilim ve Teknoloji Dergisi
Recent studies have shown that ensemble feature selection (EFS) has achieved outstanding performance in microarray data classification. However, some issues remain partially resolved, such as suboptimal aggregation methods and non-optimised underlying FS
Hüseyin Güney, Hüseyin Öztoprak
doaj   +1 more source

Random forest for gene selection and microarray data classification [PDF]

, 2011
A random forest method has been selected to perform both gene selection and classification of the microarray data. The goal of this research is to develop and improve the random forest gene selection method.
Moorthy, Kohbalan, Mohammad, Mohd. Saberi   +1 more
core   +2 more sources

Identifying functionally relevant candidate genes for inflexible ethanol intake in mice and humans using a guilt‐by‐association approach

Brain and Behavior, 2020
Gene prioritization approaches are useful tools to explore and select candidate genes in transcriptome studies. Knowing the importance of processes such as neuronal activity, intracellular signal transduction, and synapse plasticity to the development ...
Luana Martins de Carvalho, Pablo A. S. Fonseca, Isadora M. Paiva, Samara Damasceno, Agatha S. B. Pedersen, Daniel daSilva e Silva, Corinde E. Wiers, Nora D. Volkow, Ana L. Brunialti Godard   +8 more
doaj   +1 more source

Physics-based analysis of Affymetrix microarray data

, 2006
We analyze publicly available data on Affymetrix microarrays spike-in experiments on the human HGU133 chipset in which sequences are added in solution at known concentrations. The spike-in set contains sequences of bacterial, human and artificial origin.
Barkema, G. T., Carlon, E., Heim, T., Tranchevent, L. -C.   +3 more
core   +1 more source

Machine-Learning Classification Models to Predict Liver Cancer with Explainable AI to Discover Associated Genes

AppliedMath, 2023
Hepatocellular carcinoma (HCC) is the primary liver cancer that occurs the most frequently. The risk of developing HCC is highest in those with chronic liver diseases, such as cirrhosis brought on by hepatitis B or C infection and the most common type of
Md Easin Hasan, Fahad Mostafa, Md S. Hossain, Jonathon Loftin   +3 more
doaj   +1 more source

Comparison of the Performance of Random Forest and K-Nearest Neighbor in Classifying Leukemia Using Principal Component Analysis

Jurnal Sisfokom
Leukemia is the most common blood cancer in Asia, one of which is Indonesia. Leukemia can affect blood cells, bone marrow, lymph nodes and other parts of the lymphatic system.
Sriani Sriani, Muhammad Ikhsan, lailan sofinah harahap   +2 more
doaj   +1 more source

Coincidence between transcriptome analyses on different microarray platforms using a parametric framework [PDF]

, 2008
A parametric framework for the analysis of transcriptome data is demonstrated to yield coincident results when applied to data acquired using two different microarray platforms.
Tomokazu Konishi, Fumikazu Konishi, Shigeru Takasaki, Kohei Inoue, Koji Nakayama, Akihiko Konagaya, Sui Huang, T Konishi, KR Popper, S Frantz, L Harris, A Abdullah-Sayani, S Draghici, P Stafford, T Konishi, T Konishi, K Nakayama, K Sumida, K Sumida, W Kuo, E Hubbell, B Bolstad, Y Yang, T Konishi, MK Kerr, T Barrett, L Gautier   +26 more
core   +3 more sources

Analyzing microarray data using CLANS [PDF]

Bioinformatics, 2007
AbstractSummary: Analysis of microarray experiments is complicated by the huge amount of data involved. Searching for groups of co-expressed genes is akin to searching for protein families in a database as, in both cases, small subsets of genes with similar features are to be found within vast quantities of data.
Frickey, Tancred, Weiller, Georg
openaire   +3 more sources

Effective affinities in microarray data

, 2006
In the past couple of years several studies have shown that hybridization in Affymetrix DNA microarrays can be rather well understood on the basis of simple models of physical chemistry.
, Alberts B, Bloomfield V A, Burden C J Pittelkow Y Wilson S R, Carlon E, Carlon E Heim T, Deutsch J M Liang S Narayan O, E Carlon, Forman J E, G T Barkema, Halperin A, J Klein Wolterink, Lipshutz R J, Lyklema J, T Heim   +14 more
core   +1 more source