FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1996894903> ?p ?o ?g. }

• W1996894903 abstract "Applying machine learning methods on microarray gene expression profiles for disease classification problems is a popular method to derive biomarkers, i.e. sets of genes that can predict disease state or outcome. Traditional approaches where expression of genes were treated independently suffer from low prediction accuracy and difficulty of biological interpretation. Current research efforts focus on integrating information on protein interactions through biochemical pathway datasets with expression profiles to propose pathway-based classifiers that can enhance disease diagnosis and prognosis. As most of the pathway activity inference methods in literature are either unsupervised or applied on two-class datasets, there is good scope to address such limitations by proposing novel methodologies. A supervised multiclass pathway activity inference method using optimisation techniques is reported. For each pathway expression dataset, patterns of its constituent genes are summarised into one composite feature, termed pathway activity, and a novel mathematical programming model is proposed to infer this feature as a weighted linear summation of expression of its constituent genes. Gene weights are determined by the optimisation model, in a way that the resulting pathway activity has the optimal discriminative power with regards to disease phenotypes. Classification is then performed on the resulting low-dimensional pathway activity profile. The model was evaluated through a variety of published gene expression profiles that cover different types of disease. We show that not only does it improve classification accuracy, but it can also perform well in multiclass disease datasets, a limitation of other approaches from the literature. Desirable features of the model include the ability to control the maximum number of genes that may participate in determining pathway activity, which may be pre-specified by the user. Overall, this work highlights the potential of building pathway-based multi-phenotype classifiers for accurate disease diagnosis and prognosis problems." @default.
• W1996894903 created "2016-06-24" @default.
• W1996894903 creator A5016031545 @default.
• W1996894903 creator A5020943711 @default.
• W1996894903 creator A5066893635 @default.
• W1996894903 creator A5076507299 @default.
• W1996894903 date "2014-12-01" @default.
• W1996894903 modified "2023-10-09" @default.
• W1996894903 title "Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework" @default.
• W1996894903 cites W1481969187 @default.
• W1996894903 cites W1546952499 @default.
• W1996894903 cites W1727290854 @default.
• W1996894903 cites W1824079534 @default.
• W1996894903 cites W1906461790 @default.
• W1996894903 cites W1969476474 @default.
• W1996894903 cites W1972382100 @default.
• W1996894903 cites W1983463159 @default.
• W1996894903 cites W1989532420 @default.
• W1996894903 cites W1990125482 @default.
• W1996894903 cites W1992045522 @default.
• W1996894903 cites W1992567149 @default.
• W1996894903 cites W1993286543 @default.
• W1996894903 cites W1999463736 @default.
• W1996894903 cites W2006410094 @default.
• W1996894903 cites W2006649323 @default.
• W1996894903 cites W2010457001 @default.
• W1996894903 cites W2011417152 @default.
• W1996894903 cites W2023587649 @default.
• W1996894903 cites W2023931764 @default.
• W1996894903 cites W2029097756 @default.
• W1996894903 cites W2036902495 @default.
• W1996894903 cites W2040263952 @default.
• W1996894903 cites W2041880090 @default.
• W1996894903 cites W2046747076 @default.
• W1996894903 cites W2049527386 @default.
• W1996894903 cites W2058237157 @default.
• W1996894903 cites W2058451329 @default.
• W1996894903 cites W2063928888 @default.
• W1996894903 cites W2064208261 @default.
• W1996894903 cites W2069081118 @default.
• W1996894903 cites W2069620150 @default.
• W1996894903 cites W2085458975 @default.
• W1996894903 cites W2092868756 @default.
• W1996894903 cites W2096079397 @default.
• W1996894903 cites W2097795961 @default.
• W1996894903 cites W2100365251 @default.
• W1996894903 cites W2100714130 @default.
• W1996894903 cites W2102889851 @default.
• W1996894903 cites W2103017472 @default.
• W1996894903 cites W2104074461 @default.
• W1996894903 cites W2105822318 @default.
• W1996894903 cites W2106359096 @default.
• W1996894903 cites W2106393550 @default.
• W1996894903 cites W2110520112 @default.
• W1996894903 cites W2113962581 @default.
• W1996894903 cites W2115580179 @default.
• W1996894903 cites W2117004913 @default.
• W1996894903 cites W2118413367 @default.
• W1996894903 cites W2119075044 @default.
• W1996894903 cites W2121636528 @default.
• W1996894903 cites W2122552734 @default.
• W1996894903 cites W2123342417 @default.
• W1996894903 cites W2127342333 @default.
• W1996894903 cites W2128985829 @default.
• W1996894903 cites W2130410032 @default.
• W1996894903 cites W2131994307 @default.
• W1996894903 cites W2132041082 @default.
• W1996894903 cites W2133199783 @default.
• W1996894903 cites W2133990480 @default.
• W1996894903 cites W2135836598 @default.
• W1996894903 cites W2138040987 @default.
• W1996894903 cites W2140416663 @default.
• W1996894903 cites W2140469676 @default.
• W1996894903 cites W2140855509 @default.
• W1996894903 cites W2142237411 @default.
• W1996894903 cites W2147246240 @default.
• W1996894903 cites W2147343434 @default.
• W1996894903 cites W2147714160 @default.
• W1996894903 cites W2148740297 @default.
• W1996894903 cites W2150671673 @default.
• W1996894903 cites W2151040995 @default.
• W1996894903 cites W2153794402 @default.
• W1996894903 cites W2154438952 @default.
• W1996894903 cites W2154947819 @default.
• W1996894903 cites W2157132621 @default.
• W1996894903 cites W2159400887 @default.
• W1996894903 cites W2159707944 @default.
• W1996894903 cites W2161426850 @default.
• W1996894903 cites W2161775803 @default.
• W1996894903 cites W2161818848 @default.
• W1996894903 cites W2163563958 @default.
• W1996894903 cites W2166267715 @default.
• W1996894903 cites W2167119716 @default.
• W1996894903 cites W2169580085 @default.
• W1996894903 cites W4245024447 @default.
• W1996894903 cites W4300402905 @default.
• W1996894903 doi "https://doi.org/10.1186/s12859-014-0390-2" @default.
• W1996894903 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4269079" @default.
• W1996894903 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25475756" @default.
• W1996894903 hasPublicationYear "2014" @default.

• next