Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to quantitatively compare the signal-to-noise ratio of different networks, the biology they describe, and to identify the optimal network to interpret a particular genetic dataset. Via GeNets users can train a machine-learning model (Quack) to make such comparisons; and they can execute, store, and share analyses of genetic and RNA sequencing datasets.
The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods (synapse.org/LINCS_MCF10A). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.
Many proteoforms-arising from alternative splicing, post-translational modifications (PTM), or paralogous genes-have distinct biological functions, such as histone PTM proteoforms. However, their quantification by existing bottom-up mass-spectrometry (MS) methods is undermined by peptide-specific biases. To avoid these biases, we developed and implemented a first-principles model (HIquant) for quantifying proteoform stoichiometries. We characterized when MS data allow inferring proteoform stoichiometries by HIquant and derived an algorithm for optimal inference. We applied this algorithm to infer proteoform stoichiometries in two experimental systems that supported rigorous bench-marking: alkylated proteoforms spiked-in at known ratios and endogenous histone 3 PTM proteoforms quantified relative to internal heavy standards. When compared with the benchmarks, the proteoform stoichiometries interfered by HIquant without using external standards had relative error of 5-15% for simple proteoforms and 20 -30% for complex proteoforms. A HIquant server is implemented at: https://web.northeastern.edu/slavov/2014_HIquant/ https://www.mcponline.org
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FIG. 3. HIquant accurately infers stoichiometries and confidence intervals across PTM site occupancies of histone 3.A, Histone 3 peptides were quantified by SRM across 7 perturbations, and the fractional site occupancies for K4 methylation estimated by two methods: Estimates inferred by HIquant without using external standards are plotted against the corresponding estimates based on MasterMix external standards with known concentrations (29). Each marker shape corresponds to the PTM site(s) shown in the legend; methylation is denoted with "me" and acetylation with "ac" followed by the number of methyl/acetyl groups. B, The validation method from (a) was extended to another set of more complex fractional site occupancies on K9 methylation and K14 acetylation.
We describe the synthesis and preliminary study of two molecules, in which a fluorine atom is positioned proximately above the π-orbitals of a C═C bond or else wherein a C-F bond interacts in a "head on" fashion with a proximate C-H bond. The spectroscopic characteristics of these unusual interactions are documented, X-ray crystallographic analyses are reported, and theoretical calculations are employed to support the observed spectroscopy.
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