Unknown

Dataset Information

0

Computational Modeling and Treatment Identification in the Myelodysplastic Syndromes.


ABSTRACT: This review discusses the need for computational modeling in myelodysplastic syndromes (MDS) and early test results.As our evolving understanding of MDS reveals a molecularly complicated disease, the need for sophisticated computer analytics is required to keep track of the number and complex interplay among the molecular abnormalities. Computational modeling and digital drug simulations using whole exome sequencing data input have produced early results showing high accuracy in predicting treatment response to standard of care drugs. Furthermore, the computational MDS models serve as clinically relevant MDS cell lines for pre-clinical assays of investigational agents. MDS is an ideal disease for computational modeling and digital drug simulations. Current research is focused on establishing the prediction value of computational modeling. Future research will test the clinical advantage of computer-informed therapy in MDS.

SUBMITTER: Drusbosky LM 

PROVIDER: S-EPMC5670191 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

altmetric image

Publications

Computational Modeling and Treatment Identification in the Myelodysplastic Syndromes.

Drusbosky Leylah M LM   Cogle Christopher R CR  

Current hematologic malignancy reports 20171001 5


<h4>Purpose of review</h4>This review discusses the need for computational modeling in myelodysplastic syndromes (MDS) and early test results.<h4>Recent findings</h4>As our evolving understanding of MDS reveals a molecularly complicated disease, the need for sophisticated computer analytics is required to keep track of the number and complex interplay among the molecular abnormalities. Computational modeling and digital drug simulations using whole exome sequencing data input have produced early  ...[more]

Similar Datasets

| S-EPMC5729336 | biostudies-literature
| S-EPMC5967332 | biostudies-literature
| S-EPMC6142510 | biostudies-literature
| S-EPMC3855821 | biostudies-literature
| S-EPMC8453916 | biostudies-literature
| S-EPMC3716523 | biostudies-literature
2023-11-28 | GSE62853 | GEO
| S-EPMC4340482 | biostudies-literature
| S-EPMC2764862 | biostudies-literature
2023-11-28 | GSE227775 | GEO