Técnicas de análise do perfil de execução e otimização de programas em química computacional

In this paper we review the basic techniques of performance analysis within the UNIX environment that are relevant in computational chemistry, with particular emphasis on the execution profile using the gprof tool. Two case studies (in ab initio and molecular dynamics calculations) are presented in order to illustrate how execution profiling can be used to effectively identify bottlenecks and to guide source code optimization. Using these profiling and optimization techniques it was possible to obtain significant speedups (of up to 30%) in both cases.

pp-Blast: a "pseudo-parallel" Blast

We have developed a software called pp-Blast that uses the publicly available Blast package and PVM (parallel virtual machine) to partition a multi-sequence query across a set of nodes with replicated or shared databases. Benchmark tests show that pp-Blast running in a cluster of 14 PCs outperformed conventional Blast running in large servers. In addition, using pp-Blast and the cluster we were able to map all human cDNAs onto the draft of the human genome in less than 6 days. We propose here that the cost/benefit ratio of pp-Blast makes it appropriate for large-scale sequence analysis. The source code and configuration files for pp-Blast are available at http://www.ludwig.org.br/biocomp/tools/pp-blast.

Pipeline for macro- and microarray analyses

The pipeline for macro- and microarray analyses (PMmA) is a set of scripts with a web interface developed to analyze DNA array data generated by array image quantification software. PMmA is designed for use with single- or double-color array data and to work as a pipeline in five classes (data format, normalization, data analysis, clustering, and array maps). It can also be used as a plugin in the BioArray Software Environment, an open-source database for array analysis, or used in a local version of the web service. All scripts in PMmA were developed in the PERL programming language and statistical analysis functions were implemented in the R statistical language. Consequently, our package is a platform-independent software. Our algorithms can correctly select almost 90% of the differentially expressed genes, showing a superior performance compared to other methods of analysis. The pipeline software has been applied to 1536 expressed sequence tags macroarray public data of sugarcane exposed to cold for 3 to 48 h. PMmA identified thirty cold-responsive genes previously unidentified in this public dataset. Fourteen genes were up-regulated, two had a variable expression and the other fourteen were down-regulated in the treatments. These new findings certainly were a consequence of using a superior statistical analysis approach, since the original study did not take into account the dependence of data variability on the average signal intensity of each gene. The web interface, supplementary information, and the package source code are available, free, to non-commercial users at http://ipe.cbmeg.unicamp.br/pub/PMmA.

Combined selection in early generation testing of self-pollinated plants

Seven selection indexes based on the phenotypic value of the individual and the mean performance of its family were assessed for their application in breeding of self-pollinated plants. There is no clear superiority from one index to another although some show one or more negative aspects, such as favoring the selection of a top performing plant from an inferior family in detriment of an excellent plant from a superior family

The importance to update the guidelines for the use of genetic testing in noncancer patients in Brazil

The Brazilian National Regulatory Agency for Private Health Insurance and Plans has recently published a technical note defining the criteria for the coverage of genetic testing to diagnose hereditary cancer. In this study we show the case of a patient with a breast lesion and an extensive history of cancer referred to a private service of genetic counseling. The patient met both criteria for hereditary breast and colorectal cancer syndrome screening. Her private insurance denied coverage for genetic testing because she lacks current or previous cancer diagnosis. After she appealed by lawsuit, the court was favorable and the test was performed using next-generation sequencing. A deletion of MLH1 exon 8 was found. We highlight the importance to offer genetic testing using multigene analysis for noncancer patients.

Violence against adolescents: an analysis based on the categories gender and generation

Exploratory and descriptive study based on quantitative and qualitative methods that analyze the phenomenon of violence against adolescents based on gender and generational categories. The data source was reports of violence from the Curitiba Protection Network from 2010 to 2012 and semi-structured interviews with 16 sheltered adolescents. Quantitative data were analyzed using SPSS software version 20.0 and the qualitative data were subjected to content analysis. The adolescents were victims of violence in the household and outside of the family environment, as victims or viewers of violence. The violence was experienced at home, mostly toward girls, with marked overtones of gender violence. More than indicating the magnitude of the issue, this study can give information to help qualify the assistance given to victimized people and address how to face this issue.

Phosphorus extracted by ion exchange resins and mehlich-1 from oxisols (latosols) treated with different phosphorus rates and sources for varied soil-source contact periods

Despite the large number of studies addressing the quantification of phosphorus (P) availability by different extraction methods, many questions remain unanswered. The aim of this paper was to compare the effectiveness of the extractors Mehlich-1, Anionic Resin (AR) and Mixed Resin (MR), to determine the availability of P under different experimental conditions. The laboratory study was arranged in randomized blocks in a [(3 x 3 x 2) + 3] x 4 factorial design, with four replications, testing the response of three soils with different texture: a very clayey Red Latosol (LV), a sandy clay loam Red Yellow Latosol (LVA), and a sandy loam Yellow Latosol (LA), to three sources (triple superphosphate, reactive phosphate rock from Gafsa-Tunisia; and natural phosphate from Araxá-Minas Gerais) at two P rates (75 and 150 mg dm-3), plus three control treatments (each soil without P application) after four contact periods (15, 30, 60, and 120 days) of the P sources with soil. The soil acidity of LV and LVA was adjusted by raising base saturation to 60 % with the application of CaCO3 and MgCO3 at a 4:1 molar ratio (LA required no correction). These samples were maintained at field moisture capacity for 30 days. After the contact periods, the samples were collected to quantify the available P concentrations by the three extractants. In general, all three indicated that the available P-content in soils was reduced after longer contact periods with the P sources. Of the three sources, this reduction was most pronounced for triple superphosphate, intermediate for reactive phosphate, while Araxá phosphate was least sensitive to the effect of time. It was observed that AR extracted lower P levels from all three soils when the sources were phosphate rocks, while MR extracted values close to Mehlich-1 in LV (clay) and LVA (medium texture) for reactive phosphate. For Araxá phosphate, much higher P values were determined by Mehlich-1 than by the resins, because of the acidity of the extractor. For triple superphosphate, both resins extracted higher P levels than Mehlich-1, due to the consumption of this extractor, particularly when used for LV and LVA.

Automatic evaluation and data generation for analytical chemistry instrumental analysis exercises

In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.