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                        "title": "BDBM 1.0: A Desktop Application for Efficient Retrieval and Processing of High-Quality Sequence Data and Application to the Identification of the Putative Coffea S-Locus",
                        "abstract": "© 2019, International Association of Scientists in the Interdisciplinary Areas.Nowadays, bioinformatics is one of the most important areas in modern biology and the creation of high-quality scientific software supporting this recent research area is one of the core activities of many researchers. In this context, high-quality sequence datasets are needed to perform inferences on the evolution of species, genes, and gene families, or to get evidence for adaptive amino acid evolution, among others. Nevertheless, sequence data are very often spread over several databases, many useful genomes and transcriptomes are non-annotated, the available annotation is not for the desired coding sequence isoform, and/or is unlikely to be accurate. Moreover, although the FASTA text-based format is quite simple and usable by most software applications, there are a number of issues that may be critical depending on the software used to analyse such files. Therefore, researchers without training in informatics often use a fraction of all available data. The above issues can be addressed using already available software applications, but there is no easy-to-use single piece of software that allows performing all these tasks within the same graphical interface, such as the one here presented, named BDBM (Blast DataBase Manager). BDBM can be used to efficiently get gene sequences from annotated and non-annotated genomes and transcriptomes. Moreover, it can be used to look for alternatives to existing annotations and to easily create reliable custom databases. Such databases are essential to prepare high-quality datasets. The analyses that we have performed on the Coffea canephora genome using BDBM aimed at the identification of the S-locus region (that harbours the genes involved in gametophytic self-incompatibility) led to the conclusion that there are two likely regions, one on chromosome 2 (around region 6600000–6650000), and another on chromosome 5 (around 15830000–15930000). Such findings are discussed in the context of the Rubiaceae gametophytic self-incompatibility evolution.",
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                            {
                                "name": "Vazquez N."
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                            {
                                "name": "Lopez-Fernandez H."
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                                "name": "Fdez-Riverola F."
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                            {
                                "name": "Vieira J."
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                            {
                                "name": "Reboiro-Jato M."
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                        "journal": "Interdisciplinary Sciences: Computational Life Sciences"
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                        "title": "G-BLASTN: Accelerating nucleotide alignment by graphics processors",
                        "abstract": "Motivation: Since 1990, the basic local alignment search tool (BLAST) has become one of the most popular and fundamental bioinformatics tools for sequence similarity searching, receiving extensive attention from the research community. The two pioneering papers on BLAST have received over 96 000 citations. Given the huge population of BLAST users and the increasing size of sequence databases, an urgent topic of study is how to improve the speed. Recently, graphics processing units (GPUs) have been widely used as low-cost, high-performance computing platforms. The existing GPU-BLAST is a promising software tool that uses a GPU to accelerate protein sequence alignment. Unfortunately, there is still no GPU-accelerated software tool for BLAST-based nucleotide sequence alignment. Results: We developed G-BLASTN, a GPU-accelerated nucleotide alignment tool based on the widely used NCBI-BLAST. G-BLASTN can produce exactly the same results as NCBI-BLAST, and it has very similar user commands. Compared with the sequential NCBI-BLAST, G-BLASTN can achieve an overall speedup of 14.80X under 'megablast' mode. More impressively, it achieves an overall speedup of 7.15X over the multithreaded NCBI-BLAST running on 4 CPU cores. When running under 'blastn' mode, the overall speedups are 4.32X (against 1-core) and 1.56X (against 4-core). G-BLASTN also supports a pipeline mode that further improves the overall performance by up to 44% when handling a batch of queries as a whole. Currently G-BLASTN is best optimized for databases with long sequences. We plan to optimize its performance on short database sequences in our future work. © The Author 2014.",
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                            {
                                "name": "Zhao K."
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                            {
                                "name": "Chu X."
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                    "term": "Proteins",
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                        "title": "Charting the proteomes of organisms with unsequenced genomes by MALDI-quadrupole time-of-flight mass spectrometry and BLAST homology searching",
                        "abstract": "MALDI-quadrupole time-of-flight mass spectrometry was applied to identify proteins from organisms whose genomes are still unknown. The identification was carried out by successively searching a sequence database - first with a peptide mass fingerprint, then with a packet of noninterpreted MS/MS spectra, and finally with peptide sequences obtained by automated interpretation of the MS/MS spectra. A \"MS BLAST\" homology searching protocol was developed to overcome specific limitations imposed by mass spectrometric data, such as the limited accuracy of de novo sequence predictions. This approach was tested in a small-scale proteomic project involving the identification of 15 bands of gel-separated proteins from the methylotrophic yeast Pichia pastoris, whose genome has not yet been sequenced and which is only distantly related to other fungi.",
                        "citationCount": 500,
                        "authors": [
                            {
                                "name": "Shevchenko A."
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                            {
                                "name": "Sunyaev S."
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                            {
                                "name": "Loboda A."
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                            {
                                "name": "Shevchenko A."
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                            {
                                "name": "Bork P."
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                            {
                                "name": "Ens W."
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                            {
                                "name": "Standing K.G."
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                        "title": "Weighted neighbor joining: A likelihood-based approach to distance-based phylogeny reconstruction",
                        "abstract": "We introduce a distance-based phylogeny reconstruction method called 'weighted neighbor joining,' or 'Weighbor' for short. As in neighbor joining, two taxa are joined in each iteration; however, the Weighbor criterion for choosing a pair of taxa to join takes into account that errors in distance estimates are exponentially larger for longer distances. The criterion embodies a likelihood function on the distances, which are modeled as correlated Gaussian random variables with different means and variances, computed under a probabilistic model for sequence evolution. The Weighbor criterion consists of two terms, an additivity term and a positivity term, that quantify the implications of joining the pair. The first term evaluates deviations from additivity of the implied external branches, while the second term evaluates confidence that the implied internal branch has a positive branch length. Compared with maximum-likelihood phylogeny reconstruction, Weighbor is much faster, while building trees that are qualitatively and quantitatively similar. Weighbor appears to be relatively immune to the 'long branches attract' and 'long branch distracts' drawbacks observed with neighbor joining, BIONJ, and parsimony.",
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                                "name": "Bruno W.J."
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                        "title": "The mammalian gene collection",
                        "abstract": "The Mammalian Gene Collection (MGC) project is a new effort by the NIH to generate full-length complementary DNA (cDNA) resources. This project will provide publicly accessible resources to the full research community. The MGC project entails the production of libraries, sequencing, and database and repository development, as well as the support of library construction, sequencing, and analytic technologies dedicated to the goal of obtaining a full set of human and other mammalian full-length (open reading frame) sequences and clones of expressed genes.",
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