Análise e proposta de um sistema para validar a quantificação de proteoformas

A Biologia Molecular estuda a estrutura e função do material genético e seus produtos de expressão, as proteínas. Cada proteína codificada por um único gene pode ser encontrada em diversas formas moleculares, denominadas proteoformas. Tais moléculas são estudadas com o auxílio de aparelhos conhecidos como Cromatógrafo e Espectrômetro de Massa, que geram uma série de dados com o objetivo de descobrir a quantidade de cada proteoforma na amostra analisada. Atualmente, não existem sistemas estabelecidos e disseminados para quantificação dirigida de proteoformas. Uma alternativa comum é analisar manualmente os dados gerados para validar a qualidade e especificidade da quantificação de cada proteoforma. Para cada amostragem, são geradas uma ou mais centenas de dados espectrométricos. Estuda-se normalmente de cinco a 20 proteoformas por projeto. Dessa forma, são analisados milhares de gráficos por amostragem de maneira manual. O objetivo deste trabalho é propor um sistema que auxilie nesse processo de validação, verificando vários arquivos de saída do Espectrômetro de Massa por vez e gerando gráficos a partir das tabelas inseridas para melhorar a visualização dos resultados e permitir um ajuste fino nos parâmetros de seleção dos dadosMolecular biology is the branch of biology concerned with the structure and the purpose of both the genetic material and its expression products, the proteins. Each protein coded by a single gene can be found as different molecular forms, known as proteoforms. These molecules are studied using devices such as a Chromatograph and a Mass Spectrometer, that generate several data used to discover the amount of each proteoform in analyzed samples. Currently, there is no established and well-known system for targeted proteoform quantification. A common alternative is to analyze the data manually in order to validate the quality and specificity of the quantification of each proteoform. For each data set, hundreds of spectrometric datapoints are generated. Also, a single project generally focuses on studying five to 20 different proteoforms. Therefore, thousands of graphs are analyzed manually for each sample. This work aims to propose a system that aids this validation process, verifying several Mass Spectrometer output files at a time, and generating charts from the tables on these files to help visualize the results and allowing fine-tuning of the data selection parameters81 p

Neotropical freshwater fisheries : A dataset of occurrence and abundance of freshwater fishes in the Neotropics

The Neotropical region hosts 4225 freshwater fish species, ranking first among the world's most diverse regions for freshwater fishes. Our NEOTROPICAL FRESHWATER FISHES data set is the first to produce a large-scale Neotropical freshwater fish inventory, covering the entire Neotropical region from Mexico and the Caribbean in the north to the southern limits in Argentina, Paraguay, Chile, and Uruguay. We compiled 185,787 distribution records, with unique georeferenced coordinates, for the 4225 species, represented by occurrence and abundance data. The number of species for the most numerous orders are as follows: Characiformes (1289), Siluriformes (1384), Cichliformes (354), Cyprinodontiformes (245), and Gymnotiformes (135). The most recorded species was the characid Astyanax fasciatus (4696 records). We registered 116,802 distribution records for native species, compared to 1802 distribution records for nonnative species. The main aim of the NEOTROPICAL FRESHWATER FISHES data set was to make these occurrence and abundance data accessible for international researchers to develop ecological and macroecological studies, from local to regional scales, with focal fish species, families, or orders. We anticipate that the NEOTROPICAL FRESHWATER FISHES data set will be valuable for studies on a wide range of ecological processes, such as trophic cascades, fishery pressure, the effects of habitat loss and fragmentation, and the impacts of species invasion and climate change. There are no copyright restrictions on the data, and please cite this data paper when using the data in publications