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  • 05.01. Computational geophysics  (1)
  • Animal evolution  (1)
  • Oxford University Press  (1)
  • Springer Nature  (1)
  • 2020-2023  (2)
  • 2020-2020
  • 1995-1999
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  • 2020-2023  (2)
  • 2020-2020
  • 1995-1999
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  • 1
    Publication Date: 2022-10-28
    Description: From the 2010s on, pattern classification has proven an effective method for flagging alerts of volcano unrest before eruptive activity at Mt. Etna, Italy. The analysis has been applied online to volcanic tremor data, and has supported the surveillance activity of the volcano that provides timely information to Civil Protection and other authorities. However, after declaring an alert, no one knows how long the volcano unrest will last and if a climactic eruptive activity will actually begin. These are critical aspects when considering the effects of a prolonged state of alert. An example of longstanding unrest is related to the Christmas Eve eruption in 2018, which was heralded by several months of almost continuous Strombolian activity. Here, we discuss the usage of thresholds to detect conditions leading to paroxysmal activity, and the challenges associated with defining such thresholds, leveraging a dataset of 52 episodes of lava fountains occurring in 2021. We were able to identify conservative settings regarding the thresholds, allowing for an early warning of impending paroxysm in almost all cases (circa 85% for the first 4 months in 2021, and over 90% for the whole year). The chosen thresholds also proved useful to predict that a paroxysmal activity was about to end. Such information provides reliable numbers for volcanologists for their assessments, based on visual information, which may not be available in bad weather or cloudy conditions.
    Description: Project IMPACT (A multidisciplinary Insight on the kinematics and dynamics of Magmatic Processes at Mt. Etna Aimed at identifying preCursor phenomena and developing early warning sysTems). IMPACT belongs to the Progetti Dipartimentali INGV [DIP7], https://progetti.ingv.it/index.php/it/progetti-dipartimentali/vulcani/impact#informazioni-sul-progetto.
    Description: Published
    Description: 17895
    Description: 4V. Processi pre-eruttivi
    Description: JCR Journal
    Keywords: Volcanic tremor ; Volcano monitoring ; Pattern recognition ; Self Organizing maps ; Fuzzy clustering ; Mt. Etna ; 04.06. Seismology ; 04.08. Volcanology ; 05.01. Computational geophysics
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
    Publication Date: 2022-10-27
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Tassia, M. G., David, K. T., Townsend, J. P., & Halanych, K. M. TIAMMAt: leveraging biodiversity to revise protein domain models, evidence from innate immunity. Molecular Biology and Evolution, 38(12), (2021): 5806–5818, https://doi.org/10.1093/molbev/msab258.
    Description: Sequence annotation is fundamental for studying the evolution of protein families, particularly when working with nonmodel species. Given the rapid, ever-increasing number of species receiving high-quality genome sequencing, accurate domain modeling that is representative of species diversity is crucial for understanding protein family sequence evolution and their inferred function(s). Here, we describe a bioinformatic tool called Taxon-Informed Adjustment of Markov Model Attributes (TIAMMAt) which revises domain profile hidden Markov models (HMMs) by incorporating homologous domain sequences from underrepresented and nonmodel species. Using innate immunity pathways as a case study, we show that revising profile HMM parameters to directly account for variation in homologs among underrepresented species provides valuable insight into the evolution of protein families. Following adjustment by TIAMMAt, domain profile HMMs exhibit changes in their per-site amino acid state emission probabilities and insertion/deletion probabilities while maintaining the overall structure of the consensus sequence. Our results show that domain revision can heavily impact evolutionary interpretations for some families (i.e., NLR’s NACHT domain), whereas impact on other domains (e.g., rel homology domain and interferon regulatory factor domains) is minimal due to high levels of sequence conservation across the sampled phylogenetic depth (i.e., Metazoa). Importantly, TIAMMAt revises target domain models to reflect homologous sequence variation using the taxonomic distribution under consideration by the user. TIAMMAt’s flexibility to revise any subset of the Pfam database using a user-defined taxonomic pool will make it a valuable tool for future protein evolution studies, particularly when incorporating (or focusing) on nonmodel species.
    Description: This work was supported by The National Science Foundation (Grant No. IOS—1755377 to K.M.H., Rita Graze, and Elizabeth Hiltbold Schwartz), and K.T.D. was supported by The National Science Foundation’s Graduate Research Fellowship Program.
    Keywords: Protein evolution ; Domain annotation ; Animal evolution ; Innate immunity
    Repository Name: Woods Hole Open Access Server
    Type: Article
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