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We performed a systematic review of lung cancer prediction models and identified 31 articles that related to 25 distinct models, of which 11 considered epidemiological factors only and did not require a clinical input.
Also, we described in detail the families of torus canards that exist in these models, and identified the torus canard explosions.
PASA updated both the UTR regions and the gene models and identified the alternatively spliced models.
Thus, as in many published studies, we focus on the prediction performance of the models and identified representative features.
We investigated these changes in in vivo models and identified two unique MUC1-CD-dependent expressional signatures.
We therefore formulated an a priori set of models and identified the best model based on AIC (Table 4).
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These informational structures go beyond domain conceptual models and identify mostly discursive, emotional, or event structures.
Law, M. et al. Automated update, revision, and quality control of the maize genome annotations using MAKER-P improves the B73 Refgenev3 gene models and identifies new genes.
To meet this challenge, one might apply simplified models and identify suitable constraints.
The second new chapter explores the mechanics of matching models and identifies a common channel through which productivity shocks are magnified across a variety of matching models.
More basic efforts within our laboratory will focus on developing improved mouse models and identifying potential drug targets in pancreatic cancer.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com