Level Rule Name Subject Property Value WARN annotation_whitespace OBCS:0000062 IAO:0000115 A plan specification that provides a detailed outline of which measurements will be taken at what times, on which material, in what manner, and by whom. Sampling plans should be designed in such a way that the resulting data will contain a representative sample of the parameters of interest and allow for all questions, as stated in the goals, to be answered. WARN annotation_whitespace OBCS:0000118 IAO:0000115 A quantitative confidence value that expresses how many times more likely the data are under one model than the other. WARN annotation_whitespace OBCS:0000124 IAO:0000115 A statistical data analysis objective where the aim is to make inference using population sample data. WARN annotation_whitespace OBCS:0000126 IAO:0000119 WEB: http://en.wikipedia.org/wiki/Random_variable WARN annotation_whitespace OBCS:0000127 IAO:0000115 An objective specification where the aim is to collect data. WARN annotation_whitespace OBCS:0000134 IAO:0000119 WEB: http://www.stats.gla.ac.uk/steps/glossary/probability_distributions.html#contvar WARN annotation_whitespace OBCS:0000135 IAO:0000119 WEB: http://www.stats.gla.ac.uk/steps/glossary/probability_distributions.html#contvar WARN annotation_whitespace OBCS:0000140 IAO:0000115 A normalization data transformation that used to create normalized gene expression level from microarray raw data. The raw intensity values are background corrected, log2 transformed and then quantile normalized in the RMA normalization process. WARN annotation_whitespace OBCS:0000141 IAO:0000119 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC33173/http://en.wikipedia.org/wiki/Significance_analysis_of_microarrays WARN annotation_whitespace OBCS:0000142 IAO:0000119 http://en.wikipedia.org/wiki/Signal-to-noise_ratiohttp://www.ncbi.nlm.nih.gov/pubmed/10521349 WARN annotation_whitespace OBCS:0000147 IAO:0000119 http://www.pnas.org/content/102/43/15545.abstract WARN annotation_whitespace OBCS:0000164 IAO:0000119 "Storey J.D. (2007) The optimal discovery procedure: A new approach to simultaneous significance testing, Journal of the Royal Statistical Society, Series B, 69: 347-368. Storey J.D., Dai J.Y., and Leek J.T. (2007) The optimal discovery procedure for large-scale significance testing, with applications to comparative microarray experiments, Biostatistics, 8: 414-432. Leek J.T,. Monsen E.C., Dabney A.R., and Storey J.D. (2006) EDGE: Extraction and analysis of differential gene expression, Bioinformatics, 22: 507-508. Storey J.D., Xiao W., Leek J.T., Tompkins R.G., and Davis R.W. (2005) Significance analysis of time course microarray experiments, Proceedings of the National Academy of Sciences, 102: 12837-12842. " WARN annotation_whitespace OBCS:0000165 IAO:0000115 "A software that can be used to produce lists of differentially expressed genes with confidence measures attached. These lists are generated via a False Discovery Rate (FDR) method of controlling the false positives. Patterns from Gene Expression (PaGE) is more than a differential expression analysis tool. PaGE is a tool to attach descriptive, dependable, and easily interpretable expression patterns to genes across multiple conditions, each represented by a set of replicated array experiments. " WARN annotation_whitespace OBCS:0000165 IAO:0000116 The input consists of (replicated) intensities from a collection of array experiments from two or more conditions (or from a collection of direct comparisons on 2-channel arrays). The output consists of patterns, one for each row identifier in the data file. One condition is used as a reference to which the other types are compared. The length of a pattern equals the number of non-reference sample types. The symbols in the patterns are integers, where positive integers represent up-regulation as compared to the reference sample type and negative integers represent down-regulation. The patterns are based on the false discovery rates for each position in the pattern, so that the number of positive and negative symbols that appear in each position of the pattern is as descriptive as the data variability allows. The patterns generated are easily interpretable in that integers are used to represent different levels of up- or down-regulation as compared to the reference sample type. WARN annotation_whitespace OBCS:0000167 IAO:0000119 http://en.wikipedia.org/wiki/Peak_calling WARN annotation_whitespace OBCS:0000226 IAO:0000115 A data set that is an aggregate of numerical data item. WARN annotation_whitespace OBCS:0000231 IAO:0000115 A rate of deaths (in general, or due to a specific cause) that in a particular population, scaled to the size of that population, per unit of time. WARN annotation_whitespace OBCS:0000232 IAO:0000115 A rate of unit shif in a hospital. WARN annotation_whitespace OBCS:0000264 IAO:0000115 A broad class of computational algorithms that rely on repeated random sampling to obtain numerical results.The goal of Monte Carlo analysis is to trace out the structure of the distributions of model output that results from specified uncertainty distributions of model inputs and model parameters. WARN annotation_whitespace OBCS:0000330 IAO:0000115 Organizational uncertainty arose when information was lost or trapped owing to the local division of labor or the circumstances of alliances and collaborations. WARN annotation_whitespace OBCS:0000331 IAO:0000115 Technical uncertainty developed as a result of inadequate tools or ambiguous information about techniques. Technical uncertainty arose from difficulties with subjects, equipment, and procedures, including the lack of standard measurement techniques. WARN annotation_whitespace OBCS:0000343 IAO:0000115 Reducible ignorance may be resolved by conducting further research, which implies that it might be possible to somehow achieve a better understanding. WARN annotation_whitespace OBCS:0000344 IAO:0000115 Irreducible ignorance applies when neither research nor development can provide sufficient knowledge about the essential relationships. WARN annotation_whitespace OBCS:0000345 IAO:0000115 Total ignorance is the other extreme from determinism on the scale of uncertainty, which implies a deep level of uncertainty, to the extent that we do not even know that we do not know. WARN annotation_whitespace OBCS:0000346 IAO:0000115 Context uncertainty includes uncertainty about the external economic, environmental, political, social, and technological situation that forms the context for the problem being examined. The context could fall within the past, the present, or the future. WARN annotation_whitespace OBCS:0000351 IAO:0000115 Uncertainty about the external driving forces that produce changes within the system (the relevant scenario variables and policy variables) and the magnitude of the forces (the values of the scenario and policy variables). WARN annotation_whitespace OBCS:0000352 IAO:0000115 Uncertainty about the systemdata that ‘drive’ themodel and typically quantify relevant features of the reference system and its behaviour (e.g. land-use maps, data on infrastructure (roads, houses)). Uncertainty about system data is generated by a lack of knowledge of the properties (including both the deterministic and the stochastic properties) of the underlying system and deficiencies in the description of the variability that can be an inherent feature of some of the phenomena under observation. WARN annotation_whitespace OBCS:0000362 IAO:0000115 A belief is psychologically certain when the subject who has it is supremely convinced of its truth. Certainty in this sense is similar to incorrigibility, which is the property a belief has of being such that the subject is incapable of giving it up. But psychological certainty is not the same thing as incorrigibility. A belief can be certain in this sense without being incorrigible; this may happen, for example, when the subject receives a very compelling bit of counterevidence to the (previously) certain belief and gives it up for that reason. Moreover, a belief can be incorrigible without being psychologically certain. For example, a mother may be incapable of giving up the belief that her son did not commit a gruesome murder, and yet, compatible with that inextinguishable belief, she may be tortured by doubt. WARN annotation_whitespace http://purl.obolibrary.org/obo/obcs.owl dc11:contributor Chris Stoeckert @en WARN annotation_whitespace http://purl.obolibrary.org/obo/obcs.owl dc11:description OBCS stands for the Ontology of Biological and Clinical Statistics. OBCS is an ontology in the domain of biological and clinical statistics. It is aligned with the Basic Formal Ontology (BFO) and the Ontology for Biomedical Investigations (OBI). OBCS imports all possible biostatistics terms in OBI and includes many additional biostatistics terms, some of which were proposed and discussed in the OBI face-to-face workshop in Ann Arbor in 2012. @en WARN duplicate_exact_synonym OBCS:0000162 IAO:0000118 translation validity WARN duplicate_exact_synonym OBCS:0000163 IAO:0000118 translation validity WARN duplicate_exact_synonym OBCS:0000241 IAO:0000118 KS test WARN duplicate_exact_synonym OBCS:0000243 IAO:0000118 KS test WARN duplicate_exact_synonym OBCS:0000326 IAO:0000118 imprecision@en WARN duplicate_exact_synonym OBCS:0000327 IAO:0000118 imprecision@en WARN duplicate_exact_synonym OBCS:0000005 IAO:0000118 Gaussian distribution WARN duplicate_exact_synonym OBCS:0000211 IAO:0000118 Gaussian distribution WARN duplicate_exact_synonym OBCS:0000246 IAO:0000118 CMH test WARN duplicate_exact_synonym OBCS:0000247 IAO:0000118 CMH test WARN equivalent_class_axiom_no_genus OBCS:0000002 OBI:0000417 OBCS:0000127 WARN equivalent_class_axiom_no_genus OBCS:0000121 OBI:0000417 OBCS:0000124 WARN equivalent_class_axiom_no_genus OBCS:0000170 OBI:0000312 OBCS:0000169 WARN equivalent_class_axiom_no_genus OBCS:0000224 OBCS:0000223 OBCS:0000010 WARN equivalent_class_axiom_no_genus OBCS:0000225 OBCS:0000223 OBCS:0000005 WARN equivalent_class_axiom_no_genus OBCS:0000230 OBI:0000293 OBI:0000078 WARN invalid_xref OBCS:0000012 oboInOwl:hasDbXref STATO_0000036 WARN missing_definition OBCS:0000020 IAO:0000115 WARN missing_definition OBCS:0000257 IAO:0000115 WARN missing_definition OBCS:0000258 IAO:0000115 WARN missing_definition OBCS:0000262 IAO:0000115 WARN missing_definition OBCS:0000271 IAO:0000115 WARN missing_definition OBCS:0000272 IAO:0000115 WARN missing_definition OBCS:0000273 IAO:0000115 WARN missing_definition OBCS:0000275 IAO:0000115 WARN missing_definition OBCS:0000276 IAO:0000115 WARN missing_definition OBCS:0000277 IAO:0000115 WARN missing_definition OBCS:0000278 IAO:0000115 WARN missing_definition OBCS:0000279 IAO:0000115 WARN missing_definition OBCS:0000280 IAO:0000115 WARN missing_definition OBCS:0000281 IAO:0000115 WARN missing_definition OBCS:0000282 IAO:0000115 WARN missing_definition OBCS:0000283 IAO:0000115 WARN missing_definition OBCS:0000284 IAO:0000115 WARN missing_definition OBCS:0000285 IAO:0000115 WARN missing_definition OBCS:0000286 IAO:0000115 WARN missing_definition OBCS:0000287 IAO:0000115 WARN missing_definition OBCS:0000288 IAO:0000115 WARN missing_definition OBCS:0000289 IAO:0000115 WARN missing_definition OBCS:0000290 IAO:0000115 WARN missing_definition OBCS:0000291 IAO:0000115 WARN missing_definition OBCS:0000292 IAO:0000115 WARN missing_definition OBCS:0000293 IAO:0000115 WARN missing_definition OBCS:0000294 IAO:0000115 WARN missing_definition OBCS:0000295 IAO:0000115 WARN missing_definition OBCS:0000296 IAO:0000115 WARN missing_definition OBCS:0000297 IAO:0000115 WARN missing_definition OBCS:0000298 IAO:0000115 WARN missing_definition OBCS:0000299 IAO:0000115 WARN missing_definition OBCS:0000300 IAO:0000115 WARN missing_definition OBCS:0000301 IAO:0000115 WARN missing_definition OBCS:0000302 IAO:0000115 WARN missing_definition OBCS:0000303 IAO:0000115 WARN missing_definition OBCS:0000304 IAO:0000115 WARN missing_definition OBCS:0000305 IAO:0000115 WARN missing_definition OBCS:0000306 IAO:0000115 WARN missing_definition OBCS:0000307 IAO:0000115 WARN missing_definition OBCS:0000308 IAO:0000115 WARN missing_definition OBCS:0000309 IAO:0000115 WARN missing_definition OBCS:0000310 IAO:0000115 WARN missing_definition OBCS:0000311 IAO:0000115 WARN missing_definition OBCS:0000312 IAO:0000115 WARN missing_definition OBCS:0000313 IAO:0000115 WARN missing_definition OBCS:0000314 IAO:0000115 WARN missing_definition OBCS:0000315 IAO:0000115 WARN missing_definition OBCS:0000316 IAO:0000115 WARN missing_definition OBCS:0000317 IAO:0000115 WARN missing_definition OBCS:0000318 IAO:0000115 WARN missing_definition OBCS:0000324 IAO:0000115 WARN missing_definition OBCS:0000325 IAO:0000115 WARN missing_definition OBCS:0000332 IAO:0000115 WARN missing_definition OBCS:0000333 IAO:0000115 WARN missing_definition OBCS:0000334 IAO:0000115 WARN missing_definition OBCS:0000335 IAO:0000115 WARN missing_definition OBCS:0000336 IAO:0000115 WARN missing_definition OBCS:0000337 IAO:0000115 WARN missing_definition OBCS:0000350 IAO:0000115 WARN missing_definition OBCS:0000353 IAO:0000115 WARN missing_definition OBCS:0000363 IAO:0000115 WARN missing_definition OBCS:0000364 IAO:0000115 WARN missing_definition OBCS:0000365 IAO:0000115 WARN missing_definition OBCS:0000366 IAO:0000115 WARN missing_definition OBCS:0000367 IAO:0000115 WARN missing_definition OBCS:0000368 IAO:0000115 WARN missing_definition OBCS:0000369 IAO:0000115 WARN missing_definition OBCS:0000370 IAO:0000115 WARN missing_definition OBCS:0000371 IAO:0000115 WARN missing_definition OBCS:0000372 IAO:0000115 WARN missing_definition OBCS:0000373 IAO:0000115 WARN missing_definition OBCS:0000374 IAO:0000115 INFO lowercase_definition OBCS:0000319 IAO:0000115 the chaotic and unpredictable nature of natural processes INFO lowercase_definition OBCS:0000320 IAO:0000115 ‘non-rational’behaviour, discrepancies between what people say and what they actually do (cognitive dissonance), or deviations of ‘standard’ behavioural patterns (micro-level behaviour). INFO lowercase_definition OBCS:0000321 IAO:0000115 the chaotic and unpredictable nature of societal processes (macro-level behaviour). The need to consider societal and institutional processes as a major contributor to uncertainty due to variability can be inferred from various papers of Funtowicz, Ravetz, and de Marchi. INFO lowercase_definition OBCS:0000326 IAO:0000115 vagueness is associated with the lack of precise or sharp distinctions or boundaries INFO lowercase_definition OBCS:0000348 IAO:0000115 uncertainty about the form of the model itself. Model structure uncertainty arises from a lack of sufficient understanding of the system (past, present, or future) that is the subject of the policy analysis, including the behaviour of the system and the interrelationships among its elements. INFO lowercase_definition OBCS:0000349 IAO:0000115 uncertainty arising from the computer implementation of the model.Model technical uncertainty is the uncertainty generated by software or hardware errors, i.e. hidden flaws in the technical equipment. Software errors arise from bugs in software, design errors in algorithms and typing errors in model source code. Hardware errors arise from bugs, such as the bug in the early version of the Pentium processor, which gave rise to numerical error in a broad range of floating-point calculations performed on the processor.