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Titlebook: 10th International Conference on Practical Applications of Computational Biology & Bioinformatics; Mohd Saberi Mohamad,Miguel P. Rocha,Jua

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Depth and Emergence Construction,tion (NER), a BTM task, seeks to identify mentions to biological entities in texts. Dictionaries, regular expressions, natural language processing and machine learning (ML) algorithms are used in this task. Over the last years, @Note2, an open-source software framework, which includes user-friendly
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https://doi.org/10.1057/9781137378576S. That poses a major problem for computational analysis, since the majority of the methods for data mining and prediction were developed to work on feature vectors. To address this challenge, a functionality of a . has been proposed recently. It automatically converts parsable sequential input into
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https://doi.org/10.1057/9781137379641ed in literature to build machine learning classifiers for these genomic data types. However, these studies did not totally exploit the relations between the three data types. These studies also suffer from the scarcity of microArray labeled data. In this paper, we propose a new system for detecting
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(Re)Discovering University Autonomyeading to the production of isoforms called isomiRs. During our study, a PERL pipeline was developed to find all the miRs (miRNAs) and isomiRs in two sets of Next Generation Sequencing (NGS) of small RNA libraries derived from naïve and activated CD4+ T cells. Then, a differential expression analysi
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William M. Bowen,Michael Schwartzenome alignment has consequently become an increasingly important field in bioinformatics. This paper describes a novel approach for comparing two whole genomes based on fuzzy logic. Benchmarks against pre-eminent whole genome alignment systems have demonstrated that the fuzzy approach outperforms e
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