Physical Sciences and Mathematics | Open Access Articles

Process-Evaluation Of Tropospheric Humidity Simulated By General Circulation Models Using Water Vapor Isotopologues: 1. Comparison Between Models And Observations, Camille Risi, David Noone, John Worden, Christian Frankenberg, Gabriele Stiller, Michael Kiefer, Bernd Funke, Kaley Walker, Peter Bernath, Matthias Schneider, Debra Wunch, Vanessa Sherlock, Nicholas M. Deutscher, David W. Griffith, Paul O. Wennberg, Kimberly Strong, Dan Smale, Emmanuel Mahieu, Sabine Barthlott, Frank Hase, Omar Garcia, Justus Notholt, Thorsten Warneke, Geoffrey Toon, David Sayres, Sandrine Bony, Jeonghoon Lee, Derek Brown, Ryu Uemura, Christophe Sturm

Faculty of Science - Papers (Archive)

[1] The goal of this study is to determine how H2O and HDO measurements in water vapor can be used to detect and diagnose biases in the representation of processes controlling tropospheric humidity in atmospheric general circulation models (GCMs). We analyze a large number of isotopic data sets (four satellite, sixteen ground-based remote-sensing, five surface in situ and three aircraft data sets) that are sensitive to different altitudes throughout the free troposphere. Despite significant differences between data sets, we identify some observed HDO/H2O characteristics that are robust across data sets and that can be used to evaluate models. We evaluate …

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A Simple Post-Hoc Method To Add Spatial Context To Predictive Species Distribution Models, Michael B. Ashcroft, Kristine O. French, Laurie A. Chisholm

Faculty of Science - Papers (Archive)

Methods to incorporate spatial context into species distribution models (SDMs) are underutilised, with predictions usually based only on environmental space and ignoring geographic space. The goals of this study were to demonstrate a relatively simple post-hoc method to include spatial context in SDMs and to quantify the improvement over purely niche-based models. The method involved producing a standard niche-based model using established techniques, such as Maxent, and then calculating the neighbourhood average of the model output in geographic space. In effect, we tested whether the spatially averaged model output was better at predicting species distributions than the raw model output. …

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Minimotif Miner 3.0: Database Expansion And Significantly Improved Reduction Of False-Positive Predictions From Consensus Sequences., Tian Mi, Jerlin Camilus Merlin, Sandeep Deverasetty, Michael R. Gryk, Travis J. Bill, Andrew W. Brooks, Logan Lee, Viraj Rathnayake, Christian A. Ross, David P. Sargeant, Christy L. Strong, Paula Watts, Sanguthevar Rajasekaran, Martin Schiller

Life Sciences Faculty Research

Minimotif Miner (MnM available at http://minimotifminer.org or http://mnm.engr.uconn.edu) is an online database for identifying new minimotifs in protein queries. Minimotifs are short contiguous peptide sequences that have a known function in at least one protein. Here we report the third release of the MnM database which has now grown 60-fold to approximately 300,000 minimotifs. Since short minimotifs are by their nature not very complex we also summarize a new set of false-positive filters and linear regression scoring that vastly enhance minimotif prediction accuracy on a test data set. This online database can be used to predict new functions in proteins …

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Faculty of Science - Papers (Archive)

A Simple Post-Hoc Method To Add Spatial Context To Predictive Species Distribution Models, Michael B. Ashcroft, Kristine O. French, Laurie A. Chisholm

Faculty of Science - Papers (Archive)

Life Sciences Faculty Research