AIMC Topic: High-Throughput Screening Assays
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Automation of biochemical assays using an open-sourced, inexpensive robotic liquid handler.
SLAS technology
Oct 11, 2024
High Throughput Screening is crucial in pharmaceutical companies for efficient testing in drug discovery and development. Our Vaccines Analytical Research and Development (V-AR&D) department extensively uses robotic liquid handlers in their High Thro...
High-throughput and computational techniques for aptamer design.
Expert opinion on drug discovery
Oct 10, 2024
INTRODUCTION: Aptamers refer to short ssDNA/RNA sequences that target small molecules, proteins, or cells. Aptamers have significantly advanced diagnostic applications, including biosensors for detecting specific biomarkers, state-of-the-art imaging,...
The revolution in high-throughput proteomics and AI.
Science (New York, N.Y.)
Sep 26, 2024
The recent capability to measure thousands of plasma proteins from a tiny blood sample has provided a new dimension of expansive data that can advance our understanding of human health. For example, the company SomaLogic has developed the means to me...
High-throughput prediction of stalk cellulose and hemicellulose content in maize using machine learning and Fourier transform infrared spectroscopy.
Bioresource technology
Sep 23, 2024
Cellulose and hemicellulose are key cross-linked carbohydrates affecting bioethanol production in maize stalks. Traditional wet chemical methods for their detection are labor-intensive, highlighting the need for high-throughput techniques. This study...
Automated High-Throughput Atomic Force Microscopy Single-Cell Nanomechanical Assay Enabled by Deep Learning-Based Optical Image Recognition.
Nano letters
Sep 20, 2024
Mechanical forces are essential for life activities, and the mechanical phenotypes of single cells are increasingly gaining attention. Atomic force microscopy (AFM) has been a standard method for single-cell nanomechanical assays, but its efficiency ...
On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering.
Faraday discussions
Sep 11, 2024
Protein design and directed evolution have separately contributed enormously to protein engineering. Without being mutually exclusive, the former relies on computation from first principles, while the latter is a combinatorial approach based on chanc...
Antimicrobial activity of compounds identified by artificial intelligence discovery engine targeting enzymes involved in Neisseria gonorrhoeae peptidoglycan metabolism.
Biological research
Sep 5, 2024
BACKGROUND: Neisseria gonorrhoeae (Ng) causes the sexually transmitted disease gonorrhoea. There are no vaccines and infections are treated principally with antibiotics. However, gonococci rapidly develop resistance to every antibiotic class used and...
Advanced deep learning approaches enable high-throughput biological and biomedicine data analysis.
Methods (San Diego, Calif.)
Aug 21, 2024
E-pharmacophore and deep learning based high throughput virtual screening for identification of CDPK1 inhibitors of Cryptosporidium parvum.
Computational biology and chemistry
Aug 13, 2024
Cryptosporidiosis, a prevalent gastrointestinal illness worldwide, is caused by the protozoan parasite Cryptosporidium parvum. Calcium-dependent protein kinase 1 (CpCDPK1), crucial for the parasite's life cycle, serves as a promising drug target due ...
Perspectives on current approaches to virtual screening in drug discovery.
Expert opinion on drug discovery
Aug 12, 2024
INTRODUCTION: For the past two decades, virtual screening (VS) has been an efficient hit finding approach for drug discovery. Today, billions of commercially accessible compounds are routinely screened, and many successful examples of VS have been re...
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