Source 1primary paper2026MED
Toolkit/genetic Minimal Intervention Sets
genetic Minimal Intervention Sets
Also known as: gMIS, gMISs
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
Here, we present a novel formulation to calculate genetic Minimal Intervention Sets, gMISs, which incorporate both gene knockouts and knock-ins.
Usefulness & Problems
No literature-backed usefulness or problem-fit explainer has been materialized for this record yet.
Published Workflows
Objective: Compute and analyze lethal genetic intervention sets in integrated genome-scale metabolic and regulatory network models of human cells, extending beyond synthetic lethality to include knockout and knock-in interventions relevant to cancer target discovery.
Why it works: The abstract frames the approach as a way to manage the combinatorial explosion of possible lethal interventions by computing minimal intervention sets in integrated network models, then using those predictions to assess lethal interaction landscapes and compare against screen data.
synthetic lethalitysynthetic dosage lethalitytumor suppressor gene complex lethalitygenetic minimal intervention set computationintegrated genome-scale metabolic and regulatory network analysiscomparison to large-scale gene knockout screen data
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete computational method used to design, rank, or analyze an engineered system.
Mechanisms
gene knock-in perturbation modelinggene knockout perturbation modelingminimal intervention set computationsynthetic dosage lethality modelingTarget processes
recombinationselectionValidation
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
Supporting Sources
Ranked Claims
Analysis of tumor suppressors in cancer cell lines with gMIS identified lethal gene knock-in strategies.
We also analyzed tumor suppressors in cancer cell lines and identified lethal gene knock-in strategies.
Applying synthetic dosage lethality with gMIS to predict essential genes in cancer showed a significant increase in sensitivity compared with large-scale gene knockout screen data.
We applied the concept of synthetic dosage lethality to predict essential genes in cancer and demonstrated a significant increase in sensitivity when compared to large-scale gene knockout screen data.
sensitivity significant increase
gMIS captures lethal genetic interventions beyond synthetic lethality, including synthetic dosage lethality and tumor suppressor gene complexes, in human cells.
With our gMIS approach, we assessed the landscape of lethal genetic interactions in human cells, capturing interventions beyond synthetic lethality, including synthetic dosage lethality and tumor suppressor gene complexes.
The paper presents a novel gMIS formulation that calculates genetic minimal intervention sets including both gene knockouts and gene knock-ins.
Here, we present a novel formulation to calculate genetic Minimal Intervention Sets, gMISs, which incorporate both gene knockouts and knock-ins.
The gMCSpy Python package includes gMIS functionality.
The gMCSpy Python package now includes gMIS functionalities.
Approval Evidence
1 source5 linked approval claimsfirst-pass slug genetic-minimal-intervention-sets
Here, we present a novel formulation to calculate genetic Minimal Intervention Sets, gMISs, which incorporate both gene knockouts and knock-ins.
Source:
application resultsupports
Analysis of tumor suppressors in cancer cell lines with gMIS identified lethal gene knock-in strategies.
We also analyzed tumor suppressors in cancer cell lines and identified lethal gene knock-in strategies.
Source:
benchmark performancesupports
Applying synthetic dosage lethality with gMIS to predict essential genes in cancer showed a significant increase in sensitivity compared with large-scale gene knockout screen data.
We applied the concept of synthetic dosage lethality to predict essential genes in cancer and demonstrated a significant increase in sensitivity when compared to large-scale gene knockout screen data.
Source:
capabilitysupports
gMIS captures lethal genetic interventions beyond synthetic lethality, including synthetic dosage lethality and tumor suppressor gene complexes, in human cells.
With our gMIS approach, we assessed the landscape of lethal genetic interactions in human cells, capturing interventions beyond synthetic lethality, including synthetic dosage lethality and tumor suppressor gene complexes.
Source:
method introductionsupports
The paper presents a novel gMIS formulation that calculates genetic minimal intervention sets including both gene knockouts and gene knock-ins.
Here, we present a novel formulation to calculate genetic Minimal Intervention Sets, gMISs, which incorporate both gene knockouts and knock-ins.
Source:
software availabilitysupports
The gMCSpy Python package includes gMIS functionality.
The gMCSpy Python package now includes gMIS functionalities.
Source:
Comparisons
No literature-backed comparison notes have been materialized for this record yet.
Ranked Citations
- 1.