about
S100A4 and its role in metastasis – computational integration of data on biological networks.Sensitivity Analysis of the NPM-ALK Signalling Network Reveals Important Pathways for Anaplastic Large Cell Lymphoma Combination Therapy.Control and signal processing by transcriptional interference.Transcriptomic analysis reveals how a lack of potassium ions increases Sulfolobus acidocaldarius sensitivity to pH changes.RNA transcript sequencing reveals inorganic sulfur compound oxidation pathways in the acidophile Acidithiobacillus ferrivorans.S100A4 and its role in metastasis – simulations of knockout and amplification of epithelial growth factor receptor and matrix metalloproteinases.Multi-omics reveal the lifestyle of the acidophilic, mineral-oxidizing model species Leptospirillum ferriphilum(T).An interactive computer lab of the galvanic cell for students in biochemistry.Computer simulations of the signalling network in FLT3 +-acute myeloid leukaemia - indications for an optimal dosage of inhibitors against FLT3 and CDK6.A computational study of hedgehog signalling involved in basal cell carcinoma reveals the potential and limitation of combination therapy.Automated Microscopic Analysis of Metal Sulfide Colonization by Acidophilic MicroorganismsSystems Biology of Acidophile Biofilms for Efficient Metal ExtractionDeep neural networks outperform human expert's capacity in characterizing bioleaching bacterial biofilm compositionReverse engineering directed gene regulatory networks from transcriptomics and proteomics data of biomining bacterial communities with approximate Bayesian computation and steady-state signalling simulations
P50
Q30977149-F7EA5EE5-1344-4EDA-A9A0-D0097DE0B96BQ36145016-F53EC06B-A8CD-4BDD-B411-69B1FE5A01A6Q37330227-FD954023-61D1-462D-9203-14ECA4A9E573Q38380128-DFCFF861-E25A-4146-B4B4-3820A95D06B1Q38382312-A62EB6B4-5BAB-4020-8127-238C7A5E6181Q38865767-39A7B7AC-FBE9-45FF-9B1C-333A35E98999Q46259293-52A3EA3B-A1BF-4B58-A680-2C2C0BE3AD40Q48316166-79F6A9A5-87A6-4939-884D-0710E10DFADDQ54114106-003A9AF2-4A11-4F41-8EB4-760A2473BD19Q55001065-D80339F1-260F-48F8-90D9-59B9686774C3Q57469801-5DFF0905-DC39-4860-A4BD-0931E490E557Q63352018-900A479E-AF2C-4EDB-8387-E45CCF78B607Q64119176-708DC7CE-3FFC-414D-9DB4-06F0109BF6D9Q92819148-E5EA8308-5D37-4300-AB95-F2BAC7ADCCB9
P50
description
researcher ORCID ID = 0000-0002-6469-0296
@en
wetenschapper
@nl
name
Antoine Buetti-Dinh
@ast
Antoine Buetti-Dinh
@en
Antoine Buetti-Dinh
@es
Antoine Buetti-Dinh
@nl
type
label
Antoine Buetti-Dinh
@ast
Antoine Buetti-Dinh
@en
Antoine Buetti-Dinh
@es
Antoine Buetti-Dinh
@nl
prefLabel
Antoine Buetti-Dinh
@ast
Antoine Buetti-Dinh
@en
Antoine Buetti-Dinh
@es
Antoine Buetti-Dinh
@nl
P31
P496
0000-0002-6469-0296