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For: Schüttler A, Altenburger R, Ammar M, Bader-Blukott M, Jakobs G, Knapp J, Krüger J, Reiche K, Wu GM, Busch W. Map and model-moving from observation to prediction in toxicogenomics. Gigascience 2019;8:giz057. [PMID: 31140561 DOI: 10.1093/gigascience/giz057] [Cited by in Crossref: 14] [Cited by in F6Publishing: 14] [Article Influence: 4.7] [Reference Citation Analysis]
Number Citing Articles
1 Duda J, Hengstler JG, Rahnenführer J. td2pLL: An intuitive time-dose-response model for cytotoxicity data with varying exposure durations. Computational Toxicology 2022;23:100234. [DOI: 10.1016/j.comtox.2022.100234] [Reference Citation Analysis]
2 Serrap A, Saarimäki LA, Pavel A, Giudice GD, Fratello M, Cattelani L, Federico A, Laurino O, Marwah VS, Fortino V, Scala G, Sofia Kinaret PA, Greco D. Nextcast: a software suite to analyse and model toxicogenomics data. Computational and Structural Biotechnology Journal 2022. [DOI: 10.1016/j.csbj.2022.03.014] [Reference Citation Analysis]
3 Reinwald H, Alvincz J, Salinas G, Schäfers C, Hollert H, Eilebrecht S. Toxicogenomic profiling after sublethal exposure to nerve- and muscle-targeting insecticides reveals cardiac and neuronal developmental effects in zebrafish embryos. Chemosphere 2021;:132746. [PMID: 34748799 DOI: 10.1016/j.chemosphere.2021.132746] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
4 Schmidt S. Moving toward the Real World: Zebrafish Transcript Map Predicts Mixture Effects Using Single-Compound Data. Environ Health Perspect 2021;129:104001. [PMID: 34609158 DOI: 10.1289/EHP9931] [Reference Citation Analysis]
5 Shankar P, McClure RS, Waters KM, Tanguay RL. Gene co-expression network analysis in zebrafish reveals chemical class specific modules. BMC Genomics 2021;22:658. [PMID: 34517816 DOI: 10.1186/s12864-021-07940-4] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
6 Schüttler A, Jakobs G, Fix JM, Krauss M, Krüger J, Leuthold D, Altenburger R, Busch W. Transcriptome-Wide Prediction and Measurement of Combined Effects Induced by Chemical Mixture Exposure in Zebrafish Embryos. Environ Health Perspect 2021;129:47006. [PMID: 33826412 DOI: 10.1289/EHP7773] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
7 Saarimäki LA, Federico A, Lynch I, Papadiamantis AG, Tsoumanis A, Melagraki G, Afantitis A, Serra A, Greco D. Manually curated transcriptomics data collection for toxicogenomic assessment of engineered nanomaterials. Sci Data 2021;8:49. [PMID: 33558569 DOI: 10.1038/s41597-021-00808-y] [Cited by in Crossref: 8] [Cited by in F6Publishing: 8] [Article Influence: 4.0] [Reference Citation Analysis]
8 Ankley GT, Cureton P, Hoke RA, Houde M, Kumar A, Kurias J, Lanno R, McCarthy C, Newsted J, Salice CJ, Sample BE, Sepúlveda MS, Steevens J, Valsecchi S. Assessing the Ecological Risks of Per- and Polyfluoroalkyl Substances: Current State-of-the Science and a Proposed Path Forward. Environ Toxicol Chem 2021;40:564-605. [PMID: 32897586 DOI: 10.1002/etc.4869] [Cited by in Crossref: 62] [Cited by in F6Publishing: 66] [Article Influence: 20.7] [Reference Citation Analysis]
9 Jakobs G, Krüger J, Schüttler A, Altenburger R, Busch W. Mixture toxicity analysis in zebrafish embryo: a time and concentration resolved study on mixture effect predictivity. Environ Sci Eur 2020;32. [DOI: 10.1186/s12302-020-00409-3] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
10 Zhang ZD, Huang MZ, Yang YJ, Liu XW, Qin Z, Li SH, Li JY. Aspirin Eugenol Ester Attenuates Paraquat-Induced Hepatotoxicity by Inhibiting Oxidative Stress. Front Physiol 2020;11:582801. [PMID: 33192594 DOI: 10.3389/fphys.2020.582801] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 0.7] [Reference Citation Analysis]
11 Larras F, Billoir E, Scholz S, Tarkka M, Wubet T, Delignette-muller M, Schmitt-jansen M. A multi-omics concentration-response framework uncovers novel understanding of triclosan effects in the chlorophyte Scenedesmus vacuolatus. Journal of Hazardous Materials 2020;397:122727. [DOI: 10.1016/j.jhazmat.2020.122727] [Cited by in Crossref: 11] [Cited by in F6Publishing: 6] [Article Influence: 3.7] [Reference Citation Analysis]
12 Serra A, Fratello M, Del Giudice G, Saarimäki LA, Paci M, Federico A, Greco D. TinderMIX: Time-dose integrated modelling of toxicogenomics data. Gigascience 2020;9:giaa055. [PMID: 32449777 DOI: 10.1093/gigascience/giaa055] [Cited by in Crossref: 11] [Cited by in F6Publishing: 11] [Article Influence: 3.7] [Reference Citation Analysis]
13 Serra A, Fratello M, Cattelani L, Liampa I, Melagraki G, Kohonen P, Nymark P, Federico A, Kinaret PAS, Jagiello K, Ha MK, Choi JS, Sanabria N, Gulumian M, Puzyn T, Yoon TH, Sarimveis H, Grafström R, Afantitis A, Greco D. Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment. Nanomaterials (Basel) 2020;10:E708. [PMID: 32276469 DOI: 10.3390/nano10040708] [Cited by in Crossref: 24] [Cited by in F6Publishing: 24] [Article Influence: 8.0] [Reference Citation Analysis]
14 Krämer S, Busch W, Schüttler A. A Self-Organizing Map of the Fathead Minnow Liver Transcriptome to Identify Consistent Toxicogenomic Patterns across Chemical Fingerprints. Environ Toxicol Chem 2020;39:526-37. [PMID: 31820487 DOI: 10.1002/etc.4646] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]