Help: KE Relationships

I Other KER Information

References for KER

List of the literature that was cited for this KER description.

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Comments and Discussion

See here for further instructions on how to comment and contribute to the discussion.

KER History

To view detailed changes to an AOP, KE, KER, or Prototypical Stressor page, click 'View History' on the upper right hand panel menu on the page.

The user can compare  new versions of the KER to older ones. Additionally, if the user is a contributor to the KER, they may revert the current version to a previous one. The Change log lists all changes to an AOP/KE/KER/Prototypical Stressor including text changes, the date and the user who made the change.

KER Watch list

The Watch List provides a list of individual AOP, KE, KER, or Prototypical Stressor that a user is currently watching, similar to Bookmarks on an internet browser.

A-B KER Identifier and Title


When a KER is created, an ID number is automatically assigned to it. This number is used for tracking the KER in the AOP-KB.

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A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream).

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Upstream Event

The "causing" Key Event (KE) in a Key Event Relationship (KER).

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Downstream Event

The "responding" Key Event (KE) in a Key Event Relationship (KER).

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C AOPs Referencing Relationship

AOPs Referencing Relationship

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection.

Clicking on the name of the AOP in the table will bring you to the individual page for that AOP.

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E Describe the KER


The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes.

Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE.

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Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves.

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D Biological Domain of Applicability for KER

Biological Domain of Applicability Overview

Developers have the option to select one or more structured terms that help to define the biological applicability domain of the KER.

In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER.

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Taxonomic Applicability for KER

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.

In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER.

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Life Stage Applicability for KER

An indication of the the relevant life stage(s) for this KER.

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Sex Applicability for KER

An indication of the the relevant sex for this KER.

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Evidence Supporting Applicability Domains for KER

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms.

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G Evidence Supporting this KER

Evidence Summary

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP.

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Biological Plausibility

Addresses the biological rationale for a connection between KEupstream and KEdownstream. 

This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured.

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Empirical Support for Linkage

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient.

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Uncertainties or Inconsistencies

Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance.

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H Quantitative Understanding of the KER

Quantitative Understanding

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE.

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Response-response relationship

Provides sources of data that define the response-response relationships between the KEs.

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Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?).

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Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.

1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 

2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 

3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 

4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references.

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Known Feedback Loops

Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits.

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F Evidence Collection Strategy

Evidence Collection Strategy Overview

Include a description of the approach for identification and assembly of the evidence base for the KER. 

For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings.  Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.

Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible.

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