Application of frequentist and Bayesian models with extensive but low‐resolution data to assess status of endangered Athabasca River rainbow trout

2021 ◽  
Author(s):  
John R. Post ◽  
Hillary G.M. Ward ◽  
Kyle Wilson ◽  
George L. Sterling ◽  
Ariane Cantin ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Bayesian Models ◽  
Low Resolution ◽  
Athabasca River ◽  
Resolution Data

Proteins and direct methods

1991 ◽  
Vol 197 (3-4) ◽  
Author(s):  
Fan Hai-fu ◽  
Hao Quan ◽  
M. M. Woolfson
Keyword(s):  
First Principles ◽  
Figure Of Merit ◽  
Direct Methods ◽  
Large Structure ◽  
Low Resolution ◽  
Figures Of Merit ◽  
Large Structures ◽  
Resolution Data

AbstractConventional direct methods, which work so well for small structures, are less successful for macromolecules. Where it has been demonstrated that a solution might be found using direct methods it is then found that the usual figures of merit are unable to distinguish the few good sets of phases from the large number of sets generated. The reasons for the difficulties with very large structures are considered from a first-principles approach taking into account both the factors of having a large number of atoms and low resolution data. A proposal is made for trying to recognize good phase sets by taking a large structure as a sum of a number of smaller structures for each of which a conventional figure of merit can be applied.

scholarly journals Long Slit Echelle Spectroscopy of Supernova Remnants in M33

1988 ◽  
Vol 101 ◽  
pp. 193-196
Author(s):  
William P. Blair ◽  
You-Hua Chu ◽  
Robert C. Kennicutt
Keyword(s):  
Supernova Remnants ◽  
Low Resolution ◽  
Low Velocity ◽  
Line Intensities ◽  
Echelle Spectroscopy ◽  
Resolution Data

AbstractWe have obtained long slit echelle spectroscopy for 10 of the brightest supernova remnants in M33 using the KPNO 4 m telescope. The profiles at Hα indicate bulk motions in the range 100–350 km s−1 in these remnants. Nearly all of the objects show signs of contamination by low velocity H II emission at some level. This affects the line intensities measured from low resolution data and may affect diameter measurements of these remnants.

scholarly journals An overview of heavy-atom derivatization of protein crystals

2016 ◽  
Vol 72 (3) ◽  
pp. 303-318 ◽  
Author(s):  
Ashley C. W. Pike ◽  
Elspeth F. Garman ◽  
Tobias Krojer ◽  
Frank von Delft ◽  
Elisabeth P. Carpenter
Keyword(s):  
Heavy Atom ◽  
Protein Crystals ◽  
Data Sets ◽  
Low Resolution ◽  
Heavy Atoms ◽  
Density Maps ◽  
Resolution Electron ◽  
First Choice ◽  
First Time ◽  
Resolution Data

Heavy-atom derivatization is one of the oldest techniques for obtaining phase information for protein crystals and, although it is no longer the first choice, it remains a useful technique for obtaining phases for unknown structures and for low-resolution data sets. It is also valuable for confirming the chain trace in low-resolution electron-density maps. This overview provides a summary of the technique and is aimed at first-time users of the method. It includes guidelines on when to use it, which heavy atoms are most likely to work, how to prepare heavy-atom solutions, how to derivatize crystals and how to determine whether a crystal is in fact a derivative.

On the Use of low-resolution Data to Improve Structure Prediction of Proteins and Protein Complexes

2009 ◽  
Vol 5 (11) ◽  
pp. 3129-3137 ◽  
Author(s):  
Marco D’Abramo ◽  
Tim Meyer ◽  
Pau Bernadó ◽  
Carles Pons ◽  
Juan Fernández Recio ◽  
...  
Keyword(s):  
Structure Prediction ◽  
Protein Complexes ◽  
Low Resolution ◽  
Resolution Data

Constructing Tolerance Intervals for the Number of Defectives Using Both High- and Low-Resolution Data

2017 ◽  
Vol 49 (4) ◽  
pp. 354-364 ◽  
Author(s):  
Hsiuying Wang ◽  
Fugee Tsung
Keyword(s):  
Low Resolution ◽  
Tolerance Intervals ◽  
Resolution Data

scholarly journals High-resolution structures from low-resolution data

2011 ◽  
Vol 8 (9) ◽  
pp. 709-709
Keyword(s):  
High Resolution ◽  
Low Resolution ◽  
Resolution Data

Finite differences for higher order derivatives of low resolution data

2021 ◽  
Author(s):  
Subramaniam Balakrishna ◽  
William W. Schultz
Keyword(s):  
Finite Differences ◽  
Higher Order ◽  
Low Resolution ◽  
Derivatives Of ◽  
Resolution Data

Collection of very low resolution protein data

1999 ◽  
Vol 32 (6) ◽  
pp. 1183-1185 ◽  
Author(s):  
Stephen T. Miller ◽  
John D. Genova ◽  
James M. Hogle
Keyword(s):  
Low Resolution ◽  
Resolution Data

Simple modifications to a MAR 345 detector which facilitate the collection of very low resolution data are described. With these modifications, the lowest order reflections from a poliovirus crystal (c= 377.1 Å) were observed, and measurement of all reflections in typical protein cells should be routine.

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