G. Arango-Argoty

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We present a comprehensive map of over 1 million polyadenylation sites and quantify their usage in major cancers and tumor cell lines using direct RNA sequencing. We built the Expression and Polyadenylation Database to enable the visualization of the polyadenylation maps in various cancers and to facilitate the discovery of novel genes and gene isoforms(More)
The highly conserved, multifunctional YB-1 is a powerful breast cancer prognostic indicator. We report on a pervasive role for YB-1 in which it associates with thousands of nonpolyadenylated short RNAs (shyRNAs) that are further processed into small RNAs (smyRNAs). Many of these RNAs have previously been identified as functional noncoding RNAs(More)
Non-coding RNAs (ncRNAs) play major roles in development and cancer progression. To identify novel ncRNAs that may identify key pathways in breast cancer development, we performed high-throughput transcript profiling of tumor and normal matched-pair tissue samples. Initial transcriptome profiling using high-density genome-wide tiling arrays revealed changes(More)
Growing concerns regarding increasing rates of antibiotic resistance call for global monitoring efforts. Monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is of particular interest as these media can serve as sources of potential novel antibiotic resistance genes (ARGs), as hot spots for ARG exchange, and as pathways(More)
Predicting the sub-cellular localization of a protein can provide useful information to uncover its molecular functions. In this sense, numerous prediction techniques have been developed, which usually have been focused on global information of the protein or sequence alignments. However, several studies have shown that the functional nature of proteins is(More)
Predicting the localization of a protein has become a useful practice for inferring its function. Most of the reported methods to predict subcellular localizations in Gram-negative bacterial proteins have shown a low false positive rate. However, some subcellular compartmens like "periplasm" and "extracellular medium" are difficult to predict and remain(More)
Estimating the function of unknown proteins is one of the main goals in bioinformatics. In the last few years, many pattern recognition algorithms have been developed, usually focusing on global information of the protein. Conversely, predictions can be done through the identification of functional sub-sequence patterns or motifs, but most methods for(More)
Predict the function of unknown proteins is one of the principal goals in computational biology. The subcellular localization of a protein allows further understanding its structure and molecular function. Numerous prediction techniques have been developed, usually focusing on global information of the protein. But, predictions can be done through the(More)
Predicting the localization of a protein has become a useful practice for inferring its function. Most of the reported methods to predict subcellular localizations in Gram-negative bacterial proteins make use of standard protein representations that generally do not take into account the distribution of the amino acids and the structural information of the(More)
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