| scholarly article | Q13442814 |
| P2093 | author name string | Elizabeth C Considine | |
| P2860 | cites work | Why Your New Cancer Biomarker May Never Work: Recurrent Patterns and Remarkable Diversity in Biomarker Failures | Q24289009 |
| Markers for early detection of cancer: statistical guidelines for nested case-control studies | Q24804995 | ||
| Reproducibility crisis in science or unrealistic expectations? | Q56980438 | ||
| A Framework for Development of Useful Metabolomic Biomarkers and Their Effective Knowledge Translation | Q57064146 | ||
| Resequencing of 200 human exomes identifies an excess of low-frequency non-synonymous coding variants | Q57087763 | ||
| The Crisis of Reproducibility, the Denominator Problem and the Scientific Role of Multi-scale Modeling | Q57123229 | ||
| Common disorders are quantitative traits | Q57278014 | ||
| Overoptimism in cross-validation when using partial least squares-discriminant analysis for omics data: a systematic study | Q59210808 | ||
| Reproducibility Crisis: Are We Ignoring Reaction Norms? | Q89258377 | ||
| Study Design Considerations for Cancer Biomarker Discoveries | Q92090661 | ||
| Critical review of reporting of the data analysis step in metabolomics | Q92104710 | ||
| A review of validated biomarkers obtained through metabolomics | Q95542788 | ||
| Irreproducibility in Preclinical Biomedical Research: Perceptions, Uncertainties, and Knowledge Gaps | Q38699688 | ||
| What does research reproducibility mean? | Q38851031 | ||
| Navigating freely-available software tools for metabolomics analysis | Q41332699 | ||
| Evaluation of normalization methods to pave the way towards large-scale LC-MS-based metabolomics profiling experiments | Q41887560 | ||
| What is complex about complex disorders? | Q42132685 | ||
| Unite and conquer: univariate and multivariate approaches for finding differentially expressed gene sets | Q42541255 | ||
| Applying a Big Data Approach to Biomarker Discovery: Running Before We Walk? | Q43541698 | ||
| Biomarker failures | Q43573419 | ||
| 1,500 scientists lift the lid on reproducibility | Q44039870 | ||
| International differences in dialysis mortality reflect background general population atherosclerotic cardiovascular mortality | Q47177273 | ||
| Beyond disease susceptibility-Leveraging genome-wide association studies for new insights into complex disease biology | Q47653264 | ||
| Experimental Design in Clinical 'Omics Biomarker Discovery. | Q47891056 | ||
| The National Biomarker Development Alliance accelerating the translation of biomarkers to the clinic | Q48065393 | ||
| Reproducibility of preclinical animal research improves with heterogeneity of study samples. | Q55153870 | ||
| Reproducible preclinical research-Is embracing variability the answer? | Q55208976 | ||
| Contextual sensitivity in scientific reproducibility | Q28597738 | ||
| Waste, Leaks, and Failures in the Biomarker Pipeline | Q30235395 | ||
| Influence of missing values substitutes on multivariate analysis of metabolomics data | Q30434701 | ||
| Metabolomics by numbers: acquiring and understanding global metabolite data | Q30925430 | ||
| Centering, scaling, and transformations: improving the biological information content of metabolomics data | Q31043704 | ||
| Effects of imputation on correlation: implications for analysis of mass spectrometry data from multiple biological matrices | Q31047935 | ||
| Non-targeted UHPLC-MS metabolomic data processing methods: a comparative investigation of normalisation, missing value imputation, transformation and scaling | Q31086494 | ||
| Data processing for mass spectrometry-based metabolomics | Q31110739 | ||
| A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets | Q33241988 | ||
| Filtering for increased power for microarray data analysis | Q33398679 | ||
| Missing value imputation for gene expression data: computational techniques to recover missing data from available information. | Q33771648 | ||
| Cancer biomarkers: can we turn recent failures into success? | Q34176379 | ||
| State-of-the art data normalization methods improve NMR-based metabolomic analysis | Q34272167 | ||
| Normalization and missing value imputation for label-free LC-MS analysis | Q34486898 | ||
| The impact of phenotypic and genetic heterogeneity on results of genome wide association studies of complex diseases | Q35022709 | ||
| Biomarker research with prospective study designs for the early detection of cancer | Q35074051 | ||
| Metabolomics for Biomarker Discovery: Moving to the Clinic | Q35674401 | ||
| Improving the quality of biomarker discovery research: the right samples and enough of them | Q35674848 | ||
| The functional spectrum of low-frequency coding variation | Q35840674 | ||
| An argument for mechanism-based statistical inference in cancer. | Q36182146 | ||
| Design options for molecular epidemiology research within cohort studies | Q36231570 | ||
| Evaluating markers for the early detection of cancer: overview of study designs and methods | Q36421984 | ||
| Review, evaluation, and discussion of the challenges of missing value imputation for mass spectrometry-based label-free global proteomics | Q36647475 | ||
| Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting | Q36709828 | ||
| The road from discovery to clinical diagnostics: lessons learned from the first FDA-cleared in vitro diagnostic multivariate index assay of proteomic biomarkers | Q36813208 | ||
| Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design | Q36936929 | ||
| How to improve reliability and efficiency of research about molecular markers: roles of phases, guidelines, and study design | Q36999117 | ||
| Better cancer biomarker discovery through better study design | Q37310041 | ||
| Biomarker discovery for heterogeneous diseases | Q37346634 | ||
| Issues in the design of molecular and genetic epidemiologic studies | Q37653865 | ||
| A tutorial review: Metabolomics and partial least squares-discriminant analysis--a marriage of convenience or a shotgun wedding | Q38499220 | ||
| P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P433 | issue | 7 | |
| P921 | main subject | biomarker | Q864574 |
| P577 | publication date | 2019-07-02 | |
| P1433 | published in | Metabolites | Q27724046 |
| P1476 | title | The Search for Clinically Useful Biomarkers of Complex Disease: A Data Analysis Perspective | |
| P478 | volume | 9 |
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