Frontiers | Dynamic Solution Space Division-Based Methods for Calculating Reaction Deletion Strategies for Constraint-Based Metabolic Networks for Substance Production: DynCubeProd
History of MOMA
Combined burden and functional impact tests for cancer driver discovery using DriverPower | Nature Communications
GitHub - DataSlingers/MoMA: MoMA: Modern Multivariate Analysis in R
Flowchart of the method as implemented in MOMA. a Example of structure... | Download Scientific Diagram
Macrophage secretion of miR-106b-5p causes renin-dependent hypertension | Nature Communications
A modular master regulator landscape controls cancer transcriptional identity - ScienceDirect
Why Should You Switch to 4D-Proteomics™?
Integrative pathway enrichment analysis of multivariate omics data | Nature Communications
The repertoire of mutational signatures in human cancer | Nature
Mathematics | Free Full-Text | MoMA Algorithm: A Bottom-Up Modeling Procedure for a Modular System under Environmental Conditions
The MOMA flux distribution: (A) wild-type E. coli network, (B) K = 5... | Download Scientific Diagram
Group members
Mathematics | Free Full-Text | MoMA Algorithm: A Bottom-Up Modeling Procedure for a Modular System under Environmental Conditions
Silencing of long non-coding RNA Sox2ot inhibits oxidative stress and inflammation of vascular smooth muscle cells in abdominal aortic aneurysm via microRNA-145-mediated Egr1 inhibition - Figure f1 | Aging
MOMA methylation in ovarian cancer tumors. The tumor:normal ratio... | Download Scientific Diagram
MOMA Makes an Art of Targeting ATPases: The Boston-based biopharmaceutical company is making these elusive molecular machines druggable.: GEN Edge: Vol 4, No 1
Pan-cancer analysis of whole genomes | Nature
Hans Bitter - SVP, Head of Data Sciences - MOMA Therapeutics | LinkedIn
The Bioinformatics Group at MOMA
MOMA Therapeutics hiring Computational Scientist in Cambridge, Massachusetts, United States | LinkedIn
A fair experimental comparison of neural network architectures for latent representations of multi-omics for drug response prediction | BMC Bioinformatics | Full Text