Sentence examples for molecular interactions generated from inspiring English sources

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Combinatorial molecular interactions generated by pathway crosstalk and feedback loops often bypass the block caused by targeted therapies against oncogenic mutated kinases.

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Generally, how chiral molecules and chiral molecular interactions generate chiral morphologies on larger scales remains to be a fundamental problem (Turing, 1952; Brown and Wolpert, 1990; Henley, 2012).

The root hair system offers an excellent opportunity to investigate how dynamic molecular interactions generate cell morphology.

Noteworthy, PKC mutations that disrupt this intra-molecular interaction generate constitutively active forms of PKC, which are useful tools for analysing PKC functions.

Oocytes armed with pools of RNA adapted for one species, work in the sense that they can be fertilized and develop but, the initial differences in maternally stored RNAs generate subsequent dysfunctions in males because molecular interactions that generate the adult testis and subsequent spermatogenesis are misregulated due to the differences in maternally stored RNA populations.

Of the two highest-scoring molecular interaction networks generated from IPA analysis, one was associated with cell signaling, nucleic acid metabolism, and molecular transport (Figure S3), while the other network contained 12 out of 35 input nodes and was functionally associated with the cell cycle, cellular maintenance, and connective tissue development (Figure 2).

Recent molecular approaches have revealed that specific biomechanical stimuli and cell interactions generate intracellular signals that are powerful inducers or suppressors of proinflammatory and reparative genes in chondrocytes.

Recent progress in the elucidation of the molecular mechanisms of viral pathogenesis has opened up new opportunities to manipulate virus-host interactions, generating effective anti-tumor strategies.

The main focus of the present study is automatic verification of the consistency of statements about molecular interactions that have been generated by an army of uncoordinated researchers.

The mass sequence data for wheat fungus interaction generated in this study provides a powerful platform for future functional and molecular research on wheat fungus interactions.

All current methods for detecting protein– protein and other molecular interactions are capable of generating false-positive data.

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