Journament

Keyword Connections - mixture toxicity Keywords

Connection Type	Connection
Journals	Scientific reports PloS one BMC Bioinformatics Chemosphere Journal of visualized experiments : JoVE Bioinformatics methods in molecular biology (clifton, nj) journal of proteome research journal of cellular biochemistry environmental toxicology and chemistry Environmental health : a global access science source pacific symposium on biocomputing pacific symposium on biocomputing
Research Groups	No Research Group Connected
Bibliographies	[1] Systematic proteomic approach to characterize the impacts of chemical interactions on protein and cytotoxicity responses to metal mixture exposures. [2] A method for predicting protein-protein interaction types. [3] The mutational landscape of phosphorylation signaling in cancer. [4] Computational prediction of lysine acetylation proteome-wide. [5] Computational phosphorylation site prediction in plants using random forests and organism-specific instance weights. [6] Cryptic disorder: an order-disorder transformation regulates the function of nucleophosmin. [7] Bioinformatic analysis and post-translational modification crosstalk prediction of lysine acetylation. [8] PostMod: sequence based prediction of kinase-specific phosphorylation sites with indirect relationship. [9] In silico determination of intracellular glycosylation and phosphorylation sites in human selectins: implications for biological function. [10] Impacts of food contact chemicals on human health: a consensus statement. [11] A novel in-situ Toxicity Identification Evaluation (iTIE) system for determining which chemicals drive impairments at contaminated sites. [12] Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy. [13] Toxicity of biomining effluents to Daphnia magna: Acute toxicity and transcriptomic biomarkers. [14] Assessment of mixture toxicity of (tri)azoles and their hepatotoxic effects in vitro by means of omics technologies. [15] Machine learning for mixture toxicity analysis based on high-throughput printing technology [16] MITAS: A model for assessing the time-dependent risk of sequential applications of pesticides for soil organisms by consideration of exposure, degradation and mixture toxicity