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Sequence of a Euplotes crassus macronuclear DNA molecule encoding a protein with homology to a rat form-I phosphoinositide-specific phospholipase C.

A 604-base pair macronuclear DNA molecule from the hypotrichous ciliate Euplotes crassus was cloned and its DNA sequence determined. The DNA sequence contains an open reading frame capable of encoding a protein 141 amino acids in length. The putative protein contains significant sequence similarity to other eukaryotic proteins, including the rat form-I phosphoinositide-specific phospholipase-C.

Amino Acid Sequence↗

Article 5. An introduction to estimation--2: from z to t.

Provided the sample size is large enough (that is, n greater than 100), the z statistic can be used to determine the confidence interval estimation of the population mean even when the sigma is not known. In these cases the estimation of the standard error of the mean is used. The z statistic is also valid when determining the population's proportion based upon a large sample. However, when dealing with smaller samples, the z statistic is replaced by the t statistic. This makes it possible to estimate, in a population with an unknown standard deviation: The probability of getting a sample mean greater than or equal to a particular value The value of a sample mean with a particular probability of occurring The probability of getting a sample mean between two particular values The confidence interval for the estimation of the population mean can also be determined using the t statistic.

Bias↗

Mixture modeling with pairwise, instance-level class constraints.

The goal of semisupervised clustering/mixture modeling is to learn the underlying groups comprising a given data set when there is also some form of instance-level supervision available, usually in the form of labels or pairwise sample constraints. Most prior work with constraints assumes the number of classes is known, with each learned cluster assumed to be a class and, hence, subject to the given class constraints. When the number of classes is unknown or when the one-cluster-per-class assumption is not valid, the use of constraints may actually be deleterious to learning the ground-truth data groups. We address this by (1) allowing allocation of multiple mixture components to individual classes and (2) estimating both the number of components and the number of classes. We also address new class discovery, with components void of constraints treated as putative unknown classes. For both real-world and synthetic data, our method is shown to accurately estimate the number of classes and to give favorable comparison with the recent approach of Shental, Bar-Hillel, Hertz, and Weinshall (2003).

Algorithms↗

preAssemble: a tool for automatic sequencer trace data processing.

BACKGROUND: Trace or chromatogram files (raw data) are produced by automatic nucleic acid sequencing equipment or sequencers. Each file contains information which can be interpreted by specialised software to reveal the sequence (base calling). This is done by the sequencer proprietary software or publicly available programs. Depending on the size of a sequencing project the number of trace files can vary from just a few to thousands of files. Sequencing quality assessment on various criteria is important at the stage preceding clustering and contig assembly. Two major publicly available packages--Phred and Staden are used by preAssemble to perform sequence quality processing. RESULTS: The preAssemble pre-assembly sequence processing pipeline has been developed for small to large scale automatic processing of DNA sequencer chromatogram (trace) data. The Staden Package Pregap4 module and base-calling program Phred are utilized in the pipeline, which produces detailed and self-explanatory output that can be displayed with a web browser. preAssemble can be used successfully with very little previous experience, however options for parameter tuning are provided for advanced users. preAssemble runs under UNIX and LINUX operating systems. It is available for downloading and will run as stand-alone software. It can also be accessed on the Norwegian Salmon Genome Project web site where preAssemble jobs can be run on the project server. CONCLUSION: preAssemble is a tool allowing to perform quality assessment of sequences generated by automatic sequencing equipment. preAssemble is flexible since both interactive jobs on the preAssemble server and the stand alone downloadable version are available. Virtually no previous experience is necessary to run a default preAssemble job, on the other hand options for parameter tuning are provided. Consequently preAssemble can be used as efficiently for just several trace files as for large scale sequence processing.

Algorithms↗

Controlling the familywise error rate in functional neuroimaging: a comparative review.

Functional neuroimaging data embodies a massive multiple testing problem, where 100,000 correlated test statistics must be assessed. The familywise error rate, the chance of any false positives is the standard measure of Type I errors in multiple testing. In this paper we review and evaluate three approaches to thresholding images of test statistics: Bonferroni, random field and the permutation test. Owing to recent developments, improved Bonferroni procedures, such as Hochberg's methods, are now applicable to dependent data. Continuous random field methods use the smoothness of the image to adapt to the severity of the multiple testing problem. Also, increased computing power has made both permutation and bootstrap methods applicable to functional neuroimaging. We evaluate these approaches on t images using simulations and a collection of real datasets. We find that Bonferroni-related tests offer little improvement over Bonferroni, while the permutation method offers substantial improvement over the random field method for low smoothness and low degrees of freedom. We also show the limitations of trying to find an equivalent number of independent tests for an image of correlated test statistics.

Brain↗

Objectivity in psychosocial measurement: what, why, how.

This article raises and tries to answer questions concerning what objectivity in psychosocial measurement is, why it is important, and how it can be achieved. Following in the tradition of the Socratic art of maiuetics, objectivity is characterized by the separation of meaning from the geometric, metaphoric, or numeric figure carrying it, allowing an ideal and abstract entity to take on a life of its own. Examples of objective entities start from anything teachable and learnable, but for the purposes of measurement, the meter, gram, volt, and liter are paradigmatic because of their generalizability across observers, instruments, laboratories, samples, applications, etc. Objectivity is important because it is only through it that distinct conceptual entities are meaningfully distinguished. Seen from another angle, objectivity is important because it defines the conditions of the possibility of shared meaning and community. Full objectivity in psychosocial measurement can be achieved only by attending to both its methodological and its social aspects. The methodological aspect has recently achieved some notice in psychosocial measurement, especially in the form of Rasch's probabilistic conjoint models. Objectivity's social aspect has only recently been noticed by historians of science, and has not yet been systematically incorporated in any psychosocial science. An approach to achieving full objectivity in psychosocial measurement is adapted from the ASTM Standard Practice for Conducting an Interlaboratory Study to Determine the Precision of a Test Method (ASTM Committee E-11 on Statistical Methods, 1992).

Data Interpretation, Statistical↗

Striking sequence similarity among sialic acid-binding lectin, pancreatic ribonucleases, and angiogenin: possible structural and functional relationships.

We found that a sialic acid-binding lectin (SABL) from bullfrog egg bears a remarkable degree of similarity with human angiogenin and the pancreatic ribonucleases (EC 3.1.27.5). Based on (1) the conservation of several disulfide bond-forming cysteines, (2) a cluster of nonpolar residues, and (3) a number of active-site residues of bovine ribonuclease, we propose that SABL has essentially the same secondary and tertiary structures and very likely has ribonuclease activity. Other possible physiological roles are discussed.

Amino Acid Sequence↗

Interpreter of maladies: redescription mining applied to biomedical data analysis.

Comprehensive, systematic and integrated data-centric statistical approaches to disease modeling can provide powerful frameworks for understanding disease etiology. Here, one such computational framework based on redescription mining in both its incarnations, static and dynamic, is discussed. The static framework provides bioinformatic tools applicable to multifaceted datasets, containing genetic, transcriptomic, proteomic, and clinical data for diseased patients and normal subjects. The dynamic redescription framework provides systems biology tools to model complex sets of regulatory, metabolic and signaling pathways in the initiation and progression of a disease. As an example, the case of chronic fatigue syndrome (CFS) is considered, which has so far remained intractable and unpredictable in its etiology and nosology. The redescription mining approaches can be applied to the Centers for Disease Control and Prevention's Wichita (KS, USA) dataset, integrating transcriptomic, epidemiological and clinical data, and can also be used to study how pathways in the hypothalamic-pituitary-adrenal axis affect CFS patients.

Algorithms↗

[In the interests of taking one's time even when one reads a scientific article! Critical review of the literature on tooth eruption].

Nowadays everybody has access to the medical literature, not only through the libraries of the universities, but even more conveniently via Medline and Pubmed. It is very tempting only to read abstracts and summaries instead of "wasting time" by reading the whole article. Reading the article itself however enables the reader to select only these articles that have a good methodological and statistical basis. In this contribution several topics will be discussed that may help the reader to read scientific articles with a critical mind: definitions, quality of the data, study concepts, composition of the sample, control group, statistical analysis, sample size and interpretation of the results. Different items are exemplified with articles that deal with the emergence of permanent teeth.

Controlled Clinical Trials as Topic↗

[Evaluation of medical diagnostic tests: application of Bayes theorem, ROC-curve and Kappa-test] .

With the technical improvement of the sensitivity and specificity of the medical diagnostic tests the principles and methods of statistical analysis of the tests are in developing too. The technical development of the diagnostic tests and the exact statistical evaluation of the data will improve the reliability and effectiveness of the decisions for medical interventions. Application, statistical evaluation and interpretation of the Bayes theorem, ROC curve and Kappa test are presented.

Bayes Theorem↗