Directionality and borderline distance of secondary bonding on the fifth coordinate site in aluminium alkoxidesElectronic supplementary information (ESI) available: details concerning data retrieval from CSD files, list of CSD refcodes with references, selected geometrical parameters, ligand atom numbering, Figs. S1 and S2. See http://www.rsc.org/suppdata/cc/b2/b204555a/

2002 ◽  
pp. 1586-1587 ◽  
Author(s):  
Janusz Lewiński ◽  
Janusz Zachara ◽  
Iwona Justyniak
Keyword(s):  
Data Retrieval ◽  
Supplementary Information ◽  
Geometrical Parameters ◽  
Ligand Atom ◽  
Secondary Bonding

VisFeature: a stand-alone program for visualizing and analyzing statistical features of biological sequences

2019 ◽  
Author(s):  
Jun Wang ◽  
Pu-Feng Du ◽  
Xin-Yu Xue ◽  
Guang-Ping Li ◽  
Yuan-Ke Zhou ◽  
...  
Keyword(s):  
Sequence Data ◽  
Software Tool ◽  
Data Retrieval ◽  
Supplementary Information ◽  
Statistical Features ◽  
Biological Sequence ◽  
Sequence Alignments ◽  
Multiple Sequence ◽  
Source Codes ◽  
Multiple Sequence Alignments

Abstract Summary Many efforts have been made in developing bioinformatics algorithms to predict functional attributes of genes and proteins from their primary sequences. One challenge in this process is to intuitively analyze and to understand the statistical features that have been selected by heuristic or iterative methods. In this paper, we developed VisFeature, which aims to be a helpful software tool that allows the users to intuitively visualize and analyze statistical features of all types of biological sequence, including DNA, RNA and proteins. VisFeature also integrates sequence data retrieval, multiple sequence alignments and statistical feature generation functions. Availability and implementation VisFeature is a desktop application that is implemented using JavaScript/Electron and R. The source codes of VisFeature are freely accessible from the GitHub repository (https://github.com/wangjun1996/VisFeature). The binary release, which includes an example dataset, can be freely downloaded from the same GitHub repository (https://github.com/wangjun1996/VisFeature/releases). Contact [email protected] or [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Mortality Tracker: the COVID-19 case for real time web APIs as epidemiology commons

2020 ◽  
Author(s):  
Jonas S Almeida ◽  
Meredith Shiels ◽  
Praphulla Bhawsar ◽  
Bhaumik Patel ◽  
Erika Nemeth ◽  
...  
Keyword(s):  
Real Time ◽  
Causes Of Death ◽  
Data Retrieval ◽  
The United States ◽  
Supplementary Information ◽  
Server Side ◽  
All Cause Mortality ◽  
Data Commons ◽  
Time Assessment ◽  
Public Time

Abstract Motivation Mortality Tracker is an in-browser application for data wrangling, analysis, dissemination and visualization of public time series of mortality in the United States. It was developed in response to requests by epidemiologists for portable real time assessment of the effect of COVID-19 on other causes of death and all-cause mortality. This is performed by comparing 2020 real time values with observations from the same week in the previous 5 years, and by enabling the extraction of temporal snapshots of mortality series that facilitate modeling the interdependence between its causes. Results Our solution employs a scalable ‘Data Commons at Web Scale’ approach that abstracts all stages of the data cycle as in-browser components. Specifically, the data wrangling computation, not just the orchestration of data retrieval, takes place in the browser, without any requirement to download or install software. This approach, where operations that would normally be computed server-side are mapped to in-browser SDKs, is sometimes loosely described as Web APIs, a designation adopted here. Availabilityand implementation https://episphere.github.io/mortalitytracker; webcast demo: youtu.be/ZsvCe7cZzLo. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals InterMineR: an R package for InterMine databases

2019 ◽  
Vol 35 (17) ◽  
pp. 3206-3207 ◽  
Author(s):  
Konstantinos A Kyritsis ◽  
Bing Wang ◽  
Julie Sullivan ◽  
Rachel Lyne ◽  
Gos Micklem
Keyword(s):  
Data Retrieval ◽  
R Package ◽  
Supplementary Information ◽  
Programming Environment ◽  
Biological Databases ◽  
Statistical Tools ◽  
Bioconductor Project ◽  
Term Enrichment ◽  
R Programming ◽  
Downstream Analysis

Abstract Summary InterMineR is a package designed to provide a flexible interface between the R programming environment and biological databases built using the InterMine platform. The package offers access to the flexible query builder and the library of term enrichment tools of the InterMine framework, as well as interoperability with other Bioconductor packages. This facilitates automation of data retrieval tasks as well as downstream analysis with existing statistical tools in the R environment. Availability and implementation InterMineR is free and open source, released under the LGPL licence and available from the Bioconductor project and Github (https://bioconductor.org/packages/release/bioc/html/InterMineR.html, https://github.com/intermine/interMineR). Supplementary information Supplementary data are available at Bioinformatics online.

Demonstration of the Use of Tape-Recorded Information from a High Vacuum Electron Microscope

1969 ◽  
Vol 27 ◽  
pp. 218-219
Author(s):  
Richard E. Hartman ◽  
Roberta S. Hartman ◽  
Peter L. Ramos
Keyword(s):  
Information Retrieval ◽  
Electron Microscope ◽  
Magnetic Tape ◽  
High Vacuum ◽  
Data Retrieval ◽  
Electronic Information ◽  
Electronic Data ◽  
Subsequent Processing ◽  
Continuous Record

We have long felt that some form of electronic information retrieval would be more desirable than conventional photographic methods in a high vacuum electron microscope for various reasons. The most obvious of these is the fact that with electronic data retrieval the major source of gas load is removed from the instrument. An equally important reason is that if any subsequent analysis of the data is to be made, a continuous record on magnetic tape gives a much larger quantity of data and gives it in a form far more satisfactory for subsequent processing.

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