30 results about "Functional profiling" patented technology

Focused aptamer libraries are constructed in accordance with a proteome (i.e., complex mixture of native biomolecules). The libraries may be screened to identify one or more candidate aptamers with desired biological activities other than specific binding to a target. Aptamers which are selected or derivatives thereof may be used for those specific activities in biological systems. Any combination of deconvoluting a focused library (functional profiling), increasing frequencies of particular aptamers in a focused library (Laser SELEX), and decreasing frequencies of particular aptamers in a focused library (DeSELEX) may be performed prior to assaying biological activity.

PROBLEM TO BE SOLVED: To provide an anti-tag antibody chip which enables the execution of the functional analysis of protein on a solid phase with high density and high throughput regardless of the kind of protein.

The invention relates to the technical field of biological feature extraction, and is a method for extracting deep bottleneck features of heart shock signals based on deep neural networks. The heart shock signal is used as the feature extraction object, and its waveform amplitude is weak and easily subject to external interference. Synchronously collected ECG signals, using the deep neural network to mine the mechanism of deep features, and extract its deep bottleneck feature parameters. This feature uses the cardiac shock signal as the input vector, and the synchronous ECG signal as the target vector. It is trained through a pre-designed 9-layer neural network to obtain deep bottleneck features and realize the organic combination of cardiac dynamic performance and electrophysiological features. This feature takes cardiac shock signals and ECG signals, which are easier to obtain in daily life, as the research object. It can not only overcome the dependence of conventional waveform characteristic parameters on waveform fluctuations, but also improve the representation performance of a single characteristic parameter. It is an application of deep learning. A new attempt to theoretically conduct daily cardiac function analysis.

The invention discloses a method for screening neuropeptide receptors. According to the principle of statistics, P<0.05 after FDR correction of genome sequencing results is required, and the selection basis of gene differential expression multiples is the effect produced by ligand-receptor binding. The strength is proportional to the number of occupied receptors; the protein model is established by using protein homology modeling technology; the three homology modeling technologies of SWISS‑MODEL, MODELLER and PHYRE2 with the most comprehensive evaluation system are comprehensively applied to avoid the single modeling technology The quality of the model is not high; this specific implementation is in the process of molecular docking, the setting requirements of each technical parameter are clear, and the docking area is accurate. After the docking is successful, the docking needs to be optimized by geometric matching and molecular dynamics methods. The molecular force field evaluation function was used to obtain the docking complex score, and the candidate receptors were determined by comprehensive expression verification, molecular characteristics and functional analysis of neuropeptide receptors.