The invention pertains to software processes, additions, and docking approaches to Autodock Vina that speeds the rate and efficiency of analyzing ligand interactions with a receptor by cognate ligands and rewards conformations in the scoring algorithm for residue interactions that are based on the biological data. The score is multiplied by a weighting factor to control the degree of ligand-residue interactions that are considered. This multiplier is then added to the docking score for confirmation.

The invention pertains to a system for reconstructing images acquired from MR and CT scanners in a robust Gadgetron based cloud computing system. A hardware interface connects clinical imaging instruments (e.g., MR or CT scanners) with a cloud computing environment that includes image data reconstruction and processing software not limited by the computational constraints typical of static hardware with finite processor power.

This technology includes a system for automatic artifact-free measurement and visualization of tissue strain by MRI at native resolution. The investigation of regional soft tissue mechanical strain can serve as a unique indicator for different related disorders. For example, measurement of myocardial tissue during contraction can help calculate, track, and assess cardiac stress. Currently, methods such as tagging MRI (tMRI) are used for imaging soft tissue deformation. Despite being well validated, methods such as tMRI suffer from low spatial and temporal resolution.

This technology relates to a closed-loop controller that is being developed as a phone app for emotional self-regulation in real-time. There is a significant association between emotion dysregulation and symptoms of depression, anxiety, eating pathology, and substance abuse, affecting millions worldwide. Consisting of a closed-loop controller that adjusts reward values in real-time according to individual mood response, the Mood Machine Interface technology compensates for adaptation to stimuli over time allowing it to generate substantial mood changes in the user.

Scientists at NCATS have developed a novel Cellular Thermal Shift Assay (CETSA), named “Real-time CETSA” in which temperature-induced aggregation of proteins can be monitored in cells in real time across a range of compound concentrations and simultaneously across a temperature gradient in a high-throughput manner. Real-time CETSA streamlines the thermal shift assay and allows investigators to capture full aggregation profiles for every sample.

This technology includes a novel computational algorithm and software implementation to map and display biological pathways and their relationship on the surface of a globe in a three-dimensional space. Currently, biological pathways and genes are represented as two-dimensional networks, which is not effective for displaying complicated relationships between pathways and genes.

This technology relates to a software package called NIMH DAO Toolbox that uses multithreading and a unique buffer structure to shorten gaps in sample readouts. Data acquisition devices running in continuous sampling mode collect data samples at a given sampling rate. The samples are typically stored in a memory buffer and read out at a regular interval. If the sampling rate is short enough, there can be a gap between the time the first sample is acquired and the time that sample is available to the user. This gap is typically on the order of tens of milliseconds.

This invention relates to methods and algorithms that incorporate information from multiple imaging modalities to identify, estimate the size, and track the time course of brain lesions. Subjects develop brain lesions over the natural course of a disease. Currently, lesions are measured and tracked by a trained neuroradiologist using slice-by-slice inspection, a slow process that is prone to human error and hard to generalize to large observational studies.

This technology includes an automated and non-invasive assessment system called Automated Identification of subjects at risks of Multiple Sclerosis (AIMS) to assist clinicians in their diagnostic evaluation. A focus of AIMS is the ‘central vein sign’ (and other radiological findings).