Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

The invention described herein relates to novel personalized methods for treating, reducing or reversing cognitive decline utilizing a number of cognitive biological functions (factors), including metabolic parameters.

Techniques for aligning a biological sequence to a graph reference construct. The graph reference construct includes first, second, and third nodes. The techniques may include: accessing first state data indicating an extent to which each of multiple subsequences of the biological sequence matches the construct when aligned so as to end at a last position of a sequence represented by the first node; accessing second state data indicating an extent to which each of the multiple subsequences matches the construct when aligned so as to end at a last position of a sequence represented by the second node; and generating third state data using the first state data and the second state data, the third state data indicating an extent to which each of the multiple subsequences matches the construct when aligned so as to end at a first position of a sequence represented by the third node.

A method to select a protein target for therapeutic application includes accessing genomic information and protein-protein interaction (PPI) data, computing a thermodynamic measure for each protein node within the network of protein nodes, generating an energy landscape data corresponding to the network of protein nodes and the thermodynamic measure, generating a PPI subnetwork by applying a topological filtration to the energy landscape data of the PPI data, computing a first Betti number for the PPI subnetwork, sequentially removing a protein node(s) from the PPI subnetwork while replacing the previously removed node(s), computing a new Betti number for the PPI subnetwork with the protein node(s) removed, computing a change between the Betti numbers, and determining, based on the change between the Beti numbers, a most significant protein target within the PPI subnetwork.

A method and system for simulating cardiac function of a patient. A patient-specific anatomical model of at least a portion of the patient's heart is generated from medical image data. Cardiac electrophysiology potentials are calculated over a computational domain defined by the patient-specific anatomical model for each of a plurality of time steps using a patient-specific cardiac electrophysiology model. The electrophysiology potentials acting on a plurality of nodes of the computational domain are calculated in parallel for each time step. Biomechanical forces are calculated over the computational domain for each of the plurality of time steps using a cardiac biomechanical model coupled to the cardiac electrophysiology model. The biomechanical forces acting on a plurality of nodes of the computational domain are estimated in parallel for each time step. Blood flow and cardiac movement are computed at each of the plurality of time steps based on the calculated biomechanical forces.

The present disclosure provides a diagnostic method based on pairwise comparison of cancers using transcriptome expression data. In one embodiment, the method comprises the steps of: obtaining a first gene expression profile of a first cancer sample having a first cancer type; obtaining a second gene expression profile of a second cancer sample having a second cancer type, wherein the second cancer type is different from the first cancer type; comparing said first gene expression profile with said second gene expression profile; and selecting N genes that are most differentially expressed in the first and the second gene expression profiles to generate pairwise differentially expressed genes (DEGs), wherein N is an integer between 10 and 100.

Systems and methods for in silico prediction of HLA type of a patient are presented in which patient sequence reads and a reference sequence with known and distinct HLA alleles are used in a de Bruijn graph. A composite match score is then used to rank HLA alleles, thus providing a first HLA type. A second HLA type is identified by re-ranking using an adjusted composite match score.

A system stores visual content, and displays the visual content on a display unit in an undistorted, overview projection. The system receives input from a user to focus on a topic in the undistorted, overview projection, and transforms the undistorted, overview projection into a focused display showing the topic selected by the user and content related to the topic selected by the user in a continuous sequence of increasingly distorted projections. In the focused display, the content that is not related to the topic selected by the user does not move on the focused display, and the content that is related to the topic selected by the user moves towards the topic selected by the user on the focused display.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

The invention provides methods for comparing one set of genetic sequences to another without discarding any information within either set. A set of genetic sequences is represented using a directed acyclic graph (DAG) avoiding any unwarranted reduction to a linear data structure. The invention provides a way to align one sequence DAG to another to produce an alignment that can itself be stored as a DAG. DAG-to-DAG alignment is a natural choice wherever a set of genomic information consisting of more than one string needs to be compared to any non-linear reference. For example, a subpopulation DAG could be compared to a population DAG in order to compare the genetic features of that subpopulation to those of the population.