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Full-Text Articles in Physical Sciences and Mathematics
A Transformer-Based Classification System For Volcanic Seismic Signals, Cristian Bravo Roman, Cindy Mora Stock, Alexander James Hemming
A Transformer-Based Classification System For Volcanic Seismic Signals, Cristian Bravo Roman, Cindy Mora Stock, Alexander James Hemming
Undergraduate Student Research Internships Conference
Volcanic seismic signals are a key element in volcano monitoring to assess the state of unrest and a possible eruption style and timing. Different sources such as brittle fracture (volcano-tectonic - VT) or fluid movement (long period - LP) generate signals with distinct characteristics in frequency content and shape, but site effects such as attenuation or background noise make their determination difficult to the untrained eye. In cases of unrest or an eminent eruption, the amount of data would require a fast and reliable source of pre-classification to classify and catalogue to aid in the job usually done by a …
Deepnec: A Novel Alignment-Free Tool For The Characterization Of Nitrification-Related Enzymes Using Deep Learning, A Step Towards Comprehensive Understanding Of The Nitrogen Cycle, Naveen Duhan
Student Research Symposium
Abstract: Nitrification is an important microbial two-step transformation in the global nitrogen cycle, as it is the only natural process that produces nitrate within a system. The functional annotation of nitrification-related enzymes has a broad range of applications in metagenomics, agriculture, industrial biotechnology, etc. The time and resources needed for determining the function of enzymes experimentally are restrictively costly. Therefore, an accurate genome-scale computational prediction of the nitrification-related enzymes has become much more important.In this study, we developed an alignment-free computational approach to determine the nitrification-related enzymes from the sequence itself. We propose deepNEC, a novel end-to-end feature selection and …