Estimating dataset size requirements for classifying DNA microarray data.
about
Mining expressed sequence tags identifies cancer markers of clinical interestOne-step extrapolation of the prediction performance of a gene signature derived from a small studyA New Combinatorial Optimization Approach for Integrated Feature Selection Using Different Datasets: A Prostate Cancer Transcriptomic StudyA simulation-approximation approach to sample size planning for high-dimensional classification studies.Predicting classifier performance with limited training data: applications to computer-aided diagnosis in breast and prostate cancer.Robust prostate cancer marker genes emerge from direct integration of inter-study microarray data.Sample size planning for developing classifiers using high-dimensional DNA microarray data.On the statistical assessment of classifiers using DNA microarray data.Microarray data analysis: from disarray to consolidation and consensus.Improved variance estimation of classification performance via reduction of bias caused by small sample sizeModeling cancer progression via pathway dependenciesChallenges in the analysis of mass-throughput data: a technical commentary from the statistical machine learning perspective.Statistical assessment of discriminative features for protein-coding and non coding cross-species conserved sequence elements.Ovarian cancer detection from metabolomic liquid chromatography/mass spectrometry data by support vector machines.Comparative study of gene set enrichment methods.Learning curves in classification with microarray data.Addressing the challenge of defining valid proteomic biomarkers and classifiers.Determination of sample size for a multi-class classifier based on single-nucleotide polymorphisms: a volume under the surface approachOptimally splitting cases for training and testing high dimensional classifiersSupervised regularized canonical correlation analysis: integrating histologic and proteomic measurements for predicting biochemical recurrence following prostate surgeryPredicting sample size required for classification performance.Discovery and validation of gene classifiers for endocrine-disrupting chemicals in zebrafish (danio rerio).Bias correction for selecting the minimal-error classifier from many machine learning modelsThe non-negative matrix factorization toolbox for biological data mining.Determination of minimum training sample size for microarray-based cancer outcome prediction-an empirical assessment.Clinical uses of microarrays in cancer research.Gut Microbiota Dysbiosis as Risk and Premorbid Factors of IBD and IBS Along the Childhood-Adulthood Transition.Transcriptomic biomarkers for individual risk assessment in new-onset heart failure.Technology insight: Emerging techniques to predict response to preoperative chemotherapy in breast cancer.Epidemiology of intracranial meningioma.Medical Image Data and Datasets in the Era of Machine Learning-Whitepaper from the 2016 C-MIMI Meeting Dataset SessionDevelopment and Validation of Biomarker Classifiers for Treatment SelectionBiological and functional analysis of statistically significant pathways deregulated in colon cancer by using gene expression profilesMachine learning-based receiver operating characteristic (ROC) curves for crisp and fuzzy classification of DNA microarrays in cancer researchImpact of bioinformatic procedures in the development and translation of high-throughput molecular classifiers in oncology.Muscling in on microarrays.Sample size requirements for training high-dimensional risk predictors.A method for constructing a confidence bound for the actual error rate of a prediction rule in high dimensions.Cognitive Machine-Learning Algorithm for Cardiac Imaging: A Pilot Study for Differentiating Constrictive Pericarditis From Restrictive Cardiomyopathy.Cardiovascular genetic medicine: genomic assessment of prognosis and diagnosis in patients with cardiomyopathy and heart failure
P2860
Q21284250-221E4446-CC2C-4648-9653-E882702C6260Q28392088-30B8BF74-8E23-4AFA-B929-D628A7F09EF9Q28647934-CD86E3FB-D584-41D4-BAA4-30421D2341ADQ30488260-396F0054-C6B3-4625-93F9-491031A5C74FQ30955403-48E5395F-5DE8-47AC-8B07-991DED4F8C4CQ31002200-7462EAB2-321B-4ADA-A75F-DC89E78F96E4Q31036639-6E97AAF7-91C0-4DA0-A5CD-71E7E096751EQ31055386-3E04FAFC-3A47-4A7E-AEDF-FE77D9058577Q33230059-D6CEC162-EAC7-4CDA-9F4A-66E510ADF376Q33236261-F7B8F2D2-FA56-40A2-8A34-67D5F22048DFQ33320177-5C256B9B-3233-42DC-A895-A26B97898D2AQ33449305-1D7A5CA9-6045-4C0D-BD64-E0C7F530523DQ33469869-A6DE485B-07ED-4D45-83E2-41159EF0D0ECQ33495701-81E489A8-295A-4667-8B88-7D9C3FD10F1EQ33499521-5D9A819C-49C8-4A45-A7B9-FB0784B23F9EQ33532931-E930EA92-8C18-4DC4-94C7-F7C795BB7AC7Q33786157-E022FE78-5B1A-4820-A8FD-6ACD21B8BA65Q33807476-D7AD3A35-3DE5-4947-82C0-99C27617F7C2Q33866314-B9E4AF75-1275-40D8-BA14-CB26B6ECBD6BQ34105674-C89E28FD-3DD6-40DB-97E7-6D647EF4C78AQ34159704-75A91AEF-0FE8-4F05-9002-3E3496A8B3C1Q34360177-B997011C-EA9D-4295-B922-32B7FB6D4F87Q34456726-CB0E12C6-D8BA-4F2C-953E-9B4E9B60E4CAQ34670961-13EE955A-40C4-467F-8618-54044638776AQ34827732-5E055641-3CF2-46AC-B097-A9E1E49F7AFEQ35797689-0D6CDA45-ACEE-4E95-B6F3-23E81D1B5367Q35847101-D63286CF-144A-4700-9A87-BD5AE1D40D3BQ36126734-D6DEE603-FCC7-404E-8D3E-E2C55362C068Q36303851-7E21C7F7-EB15-409B-87BB-6F28927B257FQ36332389-B14B102F-3F92-4F25-86AE-7F47418ADC50Q36374528-07BC37FD-BC70-41D7-87E4-8A2AA1B80A68Q36591860-6AC8097E-A447-4652-B86B-D0E5250ABFA4Q36938166-6232A622-E924-4A6A-A7F9-387FF75557EDQ37011146-7A09C2B2-1796-4D7D-BB30-C274640DDA56Q37100056-4F3EBAE5-D342-4E7B-B5B1-93C98E9620B0Q37112545-962AF06A-EC08-4DDB-B6C8-A2624360B238Q37162810-27592DA4-3AC7-495B-9798-E06D3F4A6625Q37322069-DD380842-2BC9-44AC-BB1D-6BF2B8897030Q37660478-434B872D-185A-4975-8AFF-54B1A23553F6Q37766146-4F81CDF0-C6FC-45AD-9C43-3DE9E056A180
P2860
Estimating dataset size requirements for classifying DNA microarray data.
description
2003 nî lūn-bûn
@nan
2003 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2003 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2003年の論文
@ja
2003年論文
@yue
2003年論文
@zh-hant
2003年論文
@zh-hk
2003年論文
@zh-mo
2003年論文
@zh-tw
2003年论文
@wuu
name
Estimating dataset size requirements for classifying DNA microarray data.
@ast
Estimating dataset size requirements for classifying DNA microarray data.
@en
type
label
Estimating dataset size requirements for classifying DNA microarray data.
@ast
Estimating dataset size requirements for classifying DNA microarray data.
@en
altLabel
Estimating dataset size requirements for classifying DNA microarray data
@en
prefLabel
Estimating dataset size requirements for classifying DNA microarray data.
@ast
Estimating dataset size requirements for classifying DNA microarray data.
@en
P2093
P1476
Estimating dataset size requirements for classifying DNA microarray data.
@en
P2093
Anna Engle
Colin Campbell
Pablo Tamayo
Ryan Rifkin
Simon Rogers
Todd R Golub
P304
P356
10.1089/106652703321825928
P407
P577
2003-01-01T00:00:00Z