version_number_image
 
 

This is the evidence view. Different line colors represent the types of evidence for the association.

 
   
Your Input:
AICDA
Activation-induced cytidine deaminase (EC 3.5.4.5) (Cytidine aminohydrolase); RNA-editing deaminase involved in somatic hypermutation, gene conversion, and class-switch recombination. Required for several crucial steps of B-cell terminal differentiation necessary for efficient antibody responses (By similarity) (198 aa)
(Canis lupus)
Predicted Functional Partners:
ENSCAFG00000005419
annotation not available (306 aa)
       0.928
ENSCAFG00000014262
annotation not available (319 aa)
       0.910
UCK1
Uridine-cytidine kinase 1 (EC 2.7.1.48) (UCK 1) (Uridine monophosphokinase 1) (Cytidine monopho [...] (279 aa)
       0.908
TK2
Thymidine kinase 2, mitochondrial precursor (EC 2.7.1.21) (Mt-TK) (272 aa)
       0.899
mdN
5'(3')-deoxyribonucleotidase, mitochondrial precursor (EC 3.1.3.-) (5',3'-nucleotidase, mitocho [...] (237 aa)
       0.899
ENSCAFG00000010354
annotation not available (548 aa)
       0.899
ENSCAFG00000005294
annotation not available (242 aa)
       0.899
ENSCAFG00000003154
annotation not available (297 aa)
       0.899
ENSCAFG00000002994
annotation not available (461 aa)
       0.899
ENSCAFG00000002931
annotation not available (260 aa)
       0.899
 
  Views:                    
   Neighborhood  Fusion  Occurence  Coexpression  Experiments  Database  Textmining      Summary Network

 

Info & Parameters ...
Network Display - Nodes are either colored (if they are directly linked to the input - as in the table) or white (nodes of a higher iteration/depth). Edges, i.e. predicted functional links, consist of up to eight lines: one color for each type of evidence. Hover or click to reveal more information about the node/edge.

Active Prediction Methods:
Neighborhood Gene Fusion Co-occurrence
Co-expression Experiments Databases Textmining
 
required confidence (score): interactors shown:
or custom value: or custom limit:

additional (white) nodes         or: network depth