#36 · Systems biology
Network and generative models of AML treatment response and drug design
The dominant thread is an explicit computational model serving as the inferential core for therapeutic questions. Two AML preprints apply this to treatment and drug design: an edge-weighted digraph framework models cytarabine treatment contextuality and explores SAMHD1 inhibitors, with a web-based interface, while a metaheuristic fragment-assembly pipeline generates ligands against AlphaFold3-modeled, WGCNA-prioritized biomarkers and tests them by docking. The published gMIS work is not AML-specific. It extends minimal intervention set formulations from gMCS to knockouts and knock-ins across integrated metabolic-regulatory networks. What is new across the set is that the model structure itself, rather than only its output, becomes the analytical object.
Published papers
Beyond synthetic lethality in large-scale metabolic and regulatory network models via genetic minimal intervention set.
Introduces genetic Minimal Intervention Sets (gMISs) extending gMCS to knockouts and knock-ins in integrated metabolic-regulatory networks, predicting…
Preprints
Transcriptome-Conditioned Personalized De Novo Drug Generation for AML Using Metaheuristic Assembly and Target-Driven Filtering
Metaheuristic fragment-assembly generates AML ligands against AlphaFold3-modeled, WGCNA-prioritized biomarkers; docking-tested.
Functionalist Oncology to Model the Contextuality of Dynamics and Treatment in Acute Myeloid Leukemia
Functionalist oncology edge-weighted digraph framework models cytarabine treatment contextuality in AML, explores SAMHD1 inhibitors, and provides a web-based…
Topic history
| Date | Rank |
|---|---|
| #36 | |
| #6 | |
| #27 | |
| #9 | |
| #16 | |
| #21 | |
| #27 | |
| #18 | |
| #18 | |
| #25 | |
| #33 | |
| #25 | |
| #14 | |
| #29 | |
| #15 | |
| #9 | |
| #15 | |
| #30 | |
| #23 | |
| #31 | |
| #23 | |
| #29 | |
| #24 | |
| #9 | |
| #8 | |
| #26 | |
| #36 | |
| #29 | |
| #10 | |
| #22 | |
| #27 | |
| #12 | |
| #28 | |
| #5 | |
| #18 | |
| #17 | |
| #38 | |
| #32 |