amineptin has been researched along with thioridazine in 5 studies
| Timeframe | Studies, this research(%) | All Research% |
|---|---|---|
| pre-1990 | 0 (0.00) | 18.7374 |
| 1990's | 0 (0.00) | 18.2507 |
| 2000's | 1 (20.00) | 29.6817 |
| 2010's | 4 (80.00) | 24.3611 |
| 2020's | 0 (0.00) | 2.80 |
| Authors | Studies |
|---|---|
| Kolaczkowska, A; Kolaczkowski, M; Michalak, K; Motohashi, N | 1 |
| Barnes, JC; Bradley, P; Day, NC; Fourches, D; Reed, JZ; Tropsha, A | 1 |
| García-Mera, X; González-Díaz, H; Prado-Prado, FJ | 1 |
| Glen, RC; Lowe, R; Mitchell, JB | 1 |
| Chen, M; Hu, C; Suzuki, A; Thakkar, S; Tong, W; Yu, K | 1 |
1 review(s) available for amineptin and thioridazine
| Article | Year |
|---|---|
DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans.
Topics: Chemical and Drug Induced Liver Injury; Databases, Factual; Drug Labeling; Humans; Pharmaceutical Preparations; Risk | 2016 |
4 other study(ies) available for amineptin and thioridazine
| Article | Year |
|---|---|
New high-throughput screening assay to reveal similarities and differences in inhibitory sensitivities of multidrug ATP-binding cassette transporters.
Topics: Antifungal Agents; ATP-Binding Cassette Transporters; Fluphenazine; Fungal Proteins; Ketoconazole; Membrane Transport Proteins; Rhodamines; Saccharomyces cerevisiae; Saccharomyces cerevisiae Proteins | 2009 |
Cheminformatics analysis of assertions mined from literature that describe drug-induced liver injury in different species.
Topics: Animals; Chemical and Drug Induced Liver Injury; Cluster Analysis; Databases, Factual; Humans; MEDLINE; Mice; Models, Chemical; Molecular Conformation; Quantitative Structure-Activity Relationship | 2010 |
Multi-target spectral moment QSAR versus ANN for antiparasitic drugs against different parasite species.
Topics: Antiparasitic Agents; Molecular Structure; Neural Networks, Computer; Parasitic Diseases; Quantitative Structure-Activity Relationship; Species Specificity; Thermodynamics | 2010 |
Predicting phospholipidosis using machine learning.
Topics: Animals; Artificial Intelligence; Databases, Factual; Drug Discovery; Humans; Lipidoses; Models, Biological; Phospholipids; Support Vector Machine | 2010 |