From Bioinformatikpedia


First, we used GOPET to predict the GO terms of this protein.

Figure 1: Result of the GOPET prediction for INSL5_HUMAN

The method only predicts functional GO terms. INSL5_HUMAN has 1 annotated GO functions. The methods predicts also 1 GO function term, which can be seen on Figure 1. Therefore we decided to check if all predictions are correct.

GO term confidence prediction term prediction GOid
hormone activity 80% right right

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We used the webserver for our analysis. We decided to only trust the significant Pfam-A matches. To check if the predictions are correct we mapped the Pfam ids to the Go ids with help of a mapping website [[1]]. If a successful mapping was not possible, we compared the names of the predicted Pfam family with the names of the GO terms. If the names are similar or equal, we decided to trust the mapping.

Graphical representation of the prediction result of Pfam:

Figure 2: Result of the Pfam prediction for LAMP1_HUMAN

Pfam found two significant Pfam-A matches:

Family E-Value GOid prediction
Insulin/IGF/Relaxin family 6.7e-08 GO:0005179 right
GO:0005576 right

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ProtFun 2.2

ProtFun 2.2 does not give clear predictions if the protein belongs to this class or not, instead it gives probabilities and odd scores. We decided to make a cutoff by 2. So all classes with an odd score of 2 or higher are results for us. You can also find a "=>" sign in the result file. This sign shows the result with the highest information content. We also take this line as result, although if the odd score is lower than 2. If we only have result with a odd score lower than 2, the line with this sign is our onliest result.
Because the prediction categories are very general, it was not possible to map the GOids. Therefore, we checked the known GO annotations. If there was a hint for a category and the protein was predicted to be in this category, we decided that the prediction is right, otherwise if the known GO annotations and the categories conflict, we count the prediction as wrong.

The ProtFun Server calculated following prediction result for INSL5_HUMAN:

Functional category
Functional category Probability Odd score Prediction
Amino acid biosynthesis 0.011 0.484 right
Biosynthesis of cofactors 0.040 0.558 right
Cell envelope 0.756 => 12.393 => right
Cellular processes 0.033 0.448 right
Central intermediary metabolism 0.048 0.755 right
Engergy metabolism 0.036 0.397 right
Fatty acid metabolsim 0.016 1.265 right
Purines and Pyrimidines 0.144 0.592 right
Regulatory functions 0.014 0.087 right
Replication and Transcription 0.020 0.075 right
Translation 0.032 0.735 right
Transport and binding 0.834 2.033 right
Enzyme/non-enzyme Probability Odd score Prediction
Enzyme 0.209 0.729 right
Nonenzyme 0.791 => 1.109 => right
Enyzme class
Enzyme class Probabilty Odd score Prediction
Oxidoreductase (EC 1.-.-.-) 0.056 0.268 right
Transferase (EC 2.-.-.-) 0.031 0.091 right
Hydrolase (EC 3.-.-.-) 0.062 0.195 right
Lyase (EC 4.-.-.-) 0.020 0.430 right
Isomerase (EC 5.-.-.-) 0.010 0.321 right
Ligase (EC 6.-.-.-) 0.017 0.327 right
Gene ontology category
Gene ontology category Probability Odd score Prediction
Signal transducer 0.374 1.746 right
Receptor 0.128 0.750 right
Hormone 0.247 => 37.936 => right
Structural protein 0.001 0.041 right
Transporter 0.025 0.228 right
Ion channel 0.010 0.168 right
Volatge-gated ion channel 0.003 0.131 right
Cation channel 0.010 0.215 right
Transcription 0.054 0.425 right
Transcription regulation 0.091 0.724 right
Stress response 0.099 1.128 right
Immune response 0.178 2.090 wrong
Growth factor 0.061 4.379 wrong
Metal ion transport 0.009 0.020 right

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