/ Home
/ SUBMISSION

/ The BJNANO
/ Diamond Open Access
/ Journal Statistics
/ Editorial Board
/ Community
/ Call for papers

/ Latest Articles
/ Most accessed
/ Thematic issues
/ Volumes
/ Authors

/ Alerts

/ TWITTER
/ LINKEDIN
/ Mastodon
/ RSS FEED

Empty search

Article Type

Publication Date Range

Search Tips

This search combines search strings from the content search (i.e. "Full Text", "Author", "Title", "Abstract", or "Keywords") with "Article Type" and "Publication Date Range" using the AND operator.

Search Examples

aromatic	the word “aromatic”
aromatic aldehyde	the word “aromatic” OR “aldehyde”
+aromatic +aldehyde	both words “aromatic” AND “aldehyde”
+aromatic -aldehyde	the word “aromatic” but NOT “aldehyde”
“aromatic aldehyde”	the exact phrase “aromatic aldehyde”
benz*	words which begin with “benz”, such as “benzene” or “benzyl”
benz*yl	words that begin with “benz” and end with “yl”, such as “benzyl” or “benzoyl”
benzyl~	words that are close to the word “benzyl”, such as “benzoyl” (i.e., fuzzy search)

BROWSE
Latest Articles
Most accessed
thematic issues
volumes
authors

BROWSE

Latest Articles Most Accessed Thematic Issues Volumes Authors

Author

1 article(s) from Hastings, Janna

The eNanoMapper database for nanomaterial safety information

Nina Jeliazkova,
Charalampos Chomenidis,
Philip Doganis,
Bengt Fadeel,
Roland Grafström,
Barry Hardy,
Janna Hastings,
Markus Hegi,
Vedrin Jeliazkov,
Nikolay Kochev,
Pekka Kohonen,
Cristian R. Munteanu,
Haralambos Sarimveis,
Bart Smeets,
Pantelis Sopasakis,
Georgia Tsiliki,
David Vorgrimmler and
Egon Willighagen

Beilstein J. Nanotechnol. 2015, 6, 1609–1634, doi:10.3762/bjnano.6.165

PDF

Figure 1: Screenshot illustrating free text search finding ontology annotated database entries (e.g. protocol...

Jump to Figure 1

Figure 2: Top level substance API documentation. The “GET /substance” call is used to retrieve or search a li...

Jump to Figure 2

Figure 3: Screenshot showing a nanomaterial entry (a gold nanoparticle with the name G15.AC) and its componen...

Jump to Figure 3

Figure 4: Experimental data JSON example.

Jump to Figure 4

Figure 5: Physico-chemical and toxicity data from the NanoWiki data set.

Jump to Figure 5

Figure 6: Compound, substance and study search API documentation.

Jump to Figure 6

Figure 7: Outline of the data model: Substances are characterised by their “composition” and are identified b...

Jump to Figure 7

Figure 8: Data upload web page of the database system showing support for two file formats.

Jump to Figure 8

Figure 9: Bundle API documentation at http://enanomapper.github.io/API. A bundle is a REST resource, allowing...

Jump to Figure 9

Figure 10: Screenshot of the bundle view with the Protein Corona data set. In addition to the Substance API, w...

Jump to Figure 10

Figure 11: Physicochemical data for multi-walled carbon nanotubes. The screenshot illustrates the data model a...

Jump to Figure 11

Figure 12: Toxicity data for multi-walled carbon nanotubes. The repeated dose toxicity (inhalation) is shown i...

Jump to Figure 12

Figure 13: Screenshot showing the results of a chemical similarity query (octyl amine, SMILES CCCCCCCCN) with ...

Jump to Figure 13

Figure 14: Screenshot showing query results in the NanoWiki data set for particle sizes between 50 and 60 nm. ...

Jump to Figure 14

Figure 15: Pie chart created with d3.js and ambit.js in a web page showing that the NanoWiki and Protein Coron...

Jump to Figure 15

Figure 16: API call in ambit.js code.

Jump to Figure 16

Figure 17: Histogram of nanomaterial sizes created with d3.js and ambit.js.

Jump to Figure 17

Figure 18: Scatter plot of nanomaterial zeta potentials against the nanomaterial sizes, also created with d3.j...

Jump to Figure 18

Figure 19: Screenshot of the Jaqpot Quattro modelling web services API, compatible with the eNanoMapper API. A...

Jump to Figure 19

Figure 20: Conjoiner API: modelling-oriented information can be extracted from bundles of experimental data. D...

Jump to Figure 20

Figure 21: Example of a PMML document.

Jump to Figure 21

Figure 22: JPDI-compliant web services can be seamlessly incorporated into the eNanoMapper framework. The clie...

Jump to Figure 22

Figure 23: Algorithm API that allows to consume as well as register new algorithms (following the JPDI specifi...

Jump to Figure 23

Figure 24: A JPDI request for training.

Jump to Figure 24

Figure 25: A model returned by JPDI service in JSON format.

Jump to Figure 25

Figure 26: An example of a JSON prediction request.

Jump to Figure 26

Figure 27: Screenshot of the descriptors calculated with quantum mechanics MOPAC web service.

Jump to Figure 27

Album

Supp Info

Full Research Paper

Published 27 Jul 2015

Full text

Other Beilstein-Institut Open Science Activities

/ Help / Support & Contact / Alerts / Privacy Policy / Terms & Conditions / Impressum