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ELASPIC ΔΔG
The final Gibbs free energy change (ΔΔG) in kcal/mol is predicted using more than 70 sequential, molecular and energetic features with the Stochastic Gradient Boosting of Decision Trees algorithm.
For more information see the ELASPIC publication.
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ELASPIC2 (EL2) score
The ELASPIC2 (EL2) score is obtained using features generated by pretrained ProteinSolver and ProtBert neural networks with the Stochastic Gradient Boosting of Decision Trees algorithm and a ranking objective function.
For more information see the ELASPIC2 (EL2) publication.

Q01130.P95H

Detailed results for job #oncokb produced by ELASPIC

Q01130, Serine/arginine-rich splicing factor 2:
P95H
1
221
HNRNPA2B1, Heterogeneous nuclear ribonucleoproteins A2/B1:
1
353
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Protein: Q01130 | HNRNPA2B1 | Cofactors | All
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Q01130.P95H

Completed successfully

Protein, domain: Q01130 RRM_1

Interacting with: HNRNPA2B1 RRM_1

PDB templates used: 2qfj_A, 2qfj_B

Seq identity: 0.282, 0.250 Model score: -0.593

ELASPIC ΔΔG: 1.597

ELASPIC2 (EL2) score: 1.336

Mutation in databases: COSMIC, COSMIC, COSMIC.

Download:  PDBwt   | PDBmut

Citation


If you use these results, please cite the papers on this page.