Kernel-based data fusion and its application to protein function prediction in yeast.
about
GeneMANIA: a real-time multiple association network integration algorithm for predicting gene functionMethods for biological data integration: perspectives and challengesUsing biological networks to improve our understanding of infectious diseasesPredicting drug-target interactions using drug-drug interactionsScoring protein relationships in functional interaction networks predicted from sequence dataUsing indirect protein interactions for the prediction of Gene Ontology functions.Integrative approaches to the prediction of protein functions based on the feature selection.Combining heterogeneous data sources for accurate functional annotation of proteins.Information content and analysis methods for multi-modal high-throughput biomedical data.Finding function: evaluation methods for functional genomic data.MULTI-MODAL DATA FUSION SCHEMES FOR INTEGRATED CLASSIFICATION OF IMAGING AND NON-IMAGING BIOMEDICAL DATA.A protein domain co-occurrence network approach for predicting protein function and inferring species phylogeny.A regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data.Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosisGene function prediction using labeled and unlabeled data.Improved functional prediction of proteins by learning kernel combinations in multilabel settings.Discovering functional interaction patterns in protein-protein interaction networks.Towards structured output prediction of enzyme functionA Bayesian integration model of high-throughput proteomics and metabolomics data for improved early detection of microbial infections.Directing experimental biology: a case study in mitochondrial biogenesis.RRW: repeated random walks on genome-scale protein networks for local cluster discoveryDisease-aging network reveals significant roles of aging genes in connecting genetic diseases.Predicting gene function using hierarchical multi-label decision tree ensemblesDetecting disease associated modules and prioritizing active genes based on high throughput data.Bayesian Markov Random Field analysis for protein function prediction based on network dataPredicting gene function using few positive examples and unlabeled onesApplication of random forests methods to diabetic retinopathy classification analyses.Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context.Supervised regularized canonical correlation analysis: integrating histologic and proteomic measurements for predicting biochemical recurrence following prostate surgeryEnzML: multi-label prediction of enzyme classes using InterPro signatures.Enhanced Multi-Protocol Analysis via Intelligent Supervised Embedding (EMPrAvISE): Detecting Prostate Cancer on Multi-Parametric MRI.Classification of structural MRI images in Alzheimer's disease from the perspective of ill-posed problems.Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.Multimodal classification of Alzheimer's disease and mild cognitive impairment.Learning a Markov Logic network for supervised gene regulatory network inferenceGoing the distance for protein function prediction: a new distance metric for protein interaction networks.Alzheimer's disease risk assessment using large-scale machine learning methodsThe role of indirect connections in gene networks in predicting functionScalable prediction of compound-protein interactions using minwise hashingGene Function Prediction from Functional Association Networks Using Kernel Partial Least Squares Regression
P2860
Q24646439-1C725CF8-E67D-4EE1-88DF-16E1A2BF29A2Q26778582-E5B4A83E-8383-420D-9EAA-67493B70F66AQ27005781-DA172169-1C83-4711-AB2E-7C5E714AC6C8Q28535368-9922690A-7692-4FF2-A316-E1FB918F0E6EQ30000951-6665C2E4-5E9E-48B4-915B-6AB36FD33467Q30479593-00CC8F8A-C655-42A0-9795-8BB71B608CA0Q30492929-3CEC4DCB-A354-4F19-AD02-E9A0FE3301F3Q30604355-8D8CC3B0-559C-4ACF-A412-142F19A11A3DQ30782019-A2666010-DC06-4190-A40B-8487D4EF2F3AQ30820459-8748076F-FAF5-4B4F-9AB0-D961F0CD262EQ30897655-B22024A6-482D-4A93-8C42-CDCF53930404Q31004647-1CDD66F1-4D67-4692-9EEF-533AE4D1207BQ31042113-17DB5310-EB6D-48AE-9C5F-BFC95A76E138Q31060360-5BBFDF9B-B238-4165-A86C-FA6FBB0C6690Q31144156-A187A146-114E-4469-AC11-74CB57E55BE4Q33284249-904B1A37-37A0-4A31-8251-48E6365C1FB4Q33343113-37ED28CF-B640-47D8-A1C5-550ED40C939EQ33393989-4D914B5E-EBA4-415C-A078-559AF5E7C5CCQ33408226-3C003CF7-4B2C-4EB7-AF13-706A5F6F8376Q33419869-9E3DB530-E088-406A-AD09-84BC986C0F53Q33501387-53380E41-F19A-41A3-BD25-6F5D49ED388CQ33506605-F45CA43D-F975-4060-915B-4A46E2779EFDQ33521571-53D8ABEB-88D0-461D-95A9-E7EB4C4B3586Q33523628-DA69A2B2-2725-4251-A79F-B0DC4663F1D7Q33535782-623C4CC1-335D-44D6-97FB-526315B43D29Q33737005-2FCCEE2A-7248-4758-B9C9-99945BBCCEE9Q33773561-4691DD72-495E-43B9-A36F-A9E8593F7AF6Q33937535-520FA814-5671-4A77-96B8-8602574B36B5Q34105674-EE273A6C-D7B5-42BB-BFFB-36F990BBAD2AQ34245713-0A275076-03DE-4BF0-97F7-8AB9BE38AD99Q34295977-8B19A39C-77CC-411D-8F60-BFCB58966127Q34446784-3EB5544D-66EB-4CB6-9A10-B60D94488B21Q34606219-0505EF49-A449-4613-A302-5AA5A8F54619Q34672813-9E0B2DBC-C1D5-4571-8AAC-C6A2AE8FB972Q34985897-AB43DDF1-9D74-4C1C-8710-DEB3B7202574Q35032288-44B50548-0BF7-45D1-9FD8-049BBF80A1B4Q35046556-EFAC9203-E74C-4C69-825C-40D5E4A2B289Q35051909-4170F487-029D-4A09-98DC-F84D47316751Q35101862-F73C587F-78EA-4686-88C9-646211F39935Q35750399-9936CB54-C1CD-4F73-A3A1-1FCBEC846DE1
P2860
Kernel-based data fusion and its application to protein function prediction in yeast.
description
2004 nî lūn-bûn
@nan
2004 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2004 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2004年の論文
@ja
2004年論文
@yue
2004年論文
@zh-hant
2004年論文
@zh-hk
2004年論文
@zh-mo
2004年論文
@zh-tw
2004年论文
@wuu
name
Kernel-based data fusion and its application to protein function prediction in yeast.
@ast
Kernel-based data fusion and its application to protein function prediction in yeast.
@en
type
label
Kernel-based data fusion and its application to protein function prediction in yeast.
@ast
Kernel-based data fusion and its application to protein function prediction in yeast.
@en
prefLabel
Kernel-based data fusion and its application to protein function prediction in yeast.
@ast
Kernel-based data fusion and its application to protein function prediction in yeast.
@en
P2093
P1476
Kernel-based data fusion and its application to protein function prediction in yeast
@en
P2093
G R G Lanckriet
M I Jordan
N Cristianini
P304
P356
10.1142/9789812704856_0029
P577
2004-01-01T00:00:00Z