Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning

Abstract

With the development of advanced predictive modelling techniques, we are witnessing a steep increase in model development initiatives in genomics that employ high-end machine learning methodologies. Of particular interest are models that predict certain genomic or biological characteristics based solely on DNA sequence information. These models, however, treat the DNA sequence as a mere collection of four, A, T, G and C, letters, thus dismissing the past physico-chemical advancements in science that can enable the use of more intricate information about nucleic acid sequences. Here, we provide a comprehensive database of quantum mechanical and geometric features for all the permutations of 7-meric DNA in their representative B, A and Z conformations. The database is generated by employing the applicable high-cost and time-consuming quantum mechanical methodologies. This can thus make it seamless to associate a wealth of novel molecular features to any DNA sequence, by scanning it with a matching k-meric window and pulling the pre-computed values from our database for further use in modelling. We demonstrate the usefulness of our deposited features through their exclusive use in developing a model for A to C mutation rate constants.

Electrohydrodynamic printing for high resolution patterning of flexible electronics toward industrial applications

“…For example, SIJ Technology (Japan) introduced Super Inkjet printer via EHD technique, which can achieve ultra-precision printing at the submicron level. 145,146 Enjet Co., Ltd. (Korea) developed eMicroJet Printer 147 equipped with visual and laser measurement to repair the defect in TFT circuit for OLED panel. Recently, Wuhan National Innovation Technology Optoelectronics Equipment (NITE) has developed a series of EHD printing equipment, as shown in Figure 8.…”