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Smart Dialysis Catheter

UCLA researchers in the Department of Cardiology at UCLA’s David Geffen School of Medicine have developed a smart dialysis catheter that can measure different patient vitals in real-time to prevent hospitalizations due to renal failure.

FEAST - Fast Expectation-Maximization Microbial Source Tracking

UCLA researchers from the Department of Computer Science have developed a method to analyze large genomic data sets to quickly identify bacteria community imbalances.

Identification Of Pan-Cancer Small Cell Neuroendocrine Phenotypes And Vulnerabilities

UCLA researchers in the Department of Molecular and Medical Pharmacology have developed a classifier for the identification and treatment of small cell neuroendocrine cancers and small-round-blue cell tumors not previously identified.

4D-seq: Single Cell RNA-sequencing with in situ Spatiotemporal Information

To develop a novel imaging-based single cell RNA-sequencing (scRNA-Seq) platform that allows capturing of spatiotemporal information and cellular behavior of the sequenced cells within tissue.

DARTS: Deep Learning Augmented RNA-seq Analysis of Transcript Splicing

Researchers led by Yi Xing have developed a novel deep learning algorithm to detect alternative splicing patterns in RNA-seq data

A Method To Determine Cause Of A Cardiac Arrest And Provide Cause-Specific Decision Support In Real-Time Using Continuous Electrocardiography

Researchers led by Duc Hong Do from the Department of Cardiology at UCLA have developed an algorithm to detect the cause of cardiac arrest in a hospital setting.

A New Human-Monitor Interface For Interpreting Clinical Images

UCLA researchers in the Department of Radiological Sciences have invented a novel interactive tool that can rapidly focus and zoom on a large number of images using eye tracking technology.

Dicom/Pacs Compression Techniques

Researchers led by Xiao Hu from the Department of Surgery at UCLA have created a novel and convenient way to compress and query medical images from a PACS system.

3D Population Maps for Noninvasively Identifying Phenotypes and Pathologies in Individual Patients

UCLA researchers in the Department of Radiological Sciences have developed a novel computation system that uses large imaging datasets to aid in clinical diagnosis and prognosis.

Surfaceome Profiling Of Advanced Prostate Cancer To Identify Target Antigens For Immune-Based Therapy

Dr. Witte and colleagues at UCLA have developed a novel approach to identify surface biomarkers and targetable antigens in prostate cancer by combining multiple omics analyses across different cell lines.

Development Of A Method For Endocrine Network Discovery Uncovers Peptide Therapeutic Targets

UCLA researchers in the Division of Cardiology at the Geffen School of Medicine have developed a bioinformatics methodology to identify and functionally annotate novel endocrine pathways.

High Throughput Digital Cell Quantification Of Immune Cell Subsets Via Epigenetic Markers

UCLA researchers in the Department of Molecular, Cell, and Developmental Biology have developed a novel high-throughput method for the quantification of immune cell subtype.

Lipid-Modified Oligonucleotides For Sample Barcoding in Droplet Microfluidics-Based Single-Cell RNA Sequencing

A new strategy for barcoding single living cells using lipid-modified oligonucleotides that can vastly enhance sample multiplexing in droplet microfluidics-based RNA sequencing

“EchoCV”: A Web-Based Fully Automated Echocardiogram Interpretation System

Echo-CV is a novel, fully-automated system for analyzing images obtained from an echocardiogram that can be deployed on the web.

Global Training Of Neural Networks For Phenomic Classification

UCLA researchers in the Department of Electrical Engineering have developed a high-throughput, label-free cell classification method based on time-stretch quantitative phase imaging.

Reducing Computational Complexity of Training Algorithms for Artificial Neural Networks

Researchers at UCLA have developed a novel mathematical theorem to revolutionize the training of large-scale artificial neural networks (ANN).

Hemodynamically Responsive Retrograde Endovascular Balloon Occlusion Of The Aorta (REBOA) Simulator

Researchers at the University of California, Davis have developed a hemodynamically responsive simulator for retrograde endovascular balloon occlusion of the aorta (REBOA).

Super Alarm – A Learning Software for Prevention of Alarm Fatigue

A robust learning software platform capable of combining both patient physiologic monitor alarms and data in EMR (e.g., laboratory tests) to more precisely monitor patients.

Sequence Independent and Ordered Nucleic Acid Assembly

Currently DNA fragments are assembled from smaller oligonucleotides that contain overlapping DNA sequences.After overlapping sequences are annealed, each oligo will act as primer for polymerization, eventually fusing the two fragments together. This method relies on unique overlapping sequences that are favorable to anneal at a specific temperature.This strategy becomes problematic when you try to assemble more than two fragments, when the uniqueness of annealing sequences, the correct order of fragments annealing and optimal temperature for all the annealing reactions are major concerns.On the other hand, annealing only two fragments at a time is time consuming and low in scalability.There is a great need for a cost-effective and accurate approach.

Integrative Approach for the Analysis and Visualization of Static or Dynamic Omic Data, Including Genomic, Proteomic, Gene Expression, and Metabolic Data

The technology is a method for analysis and mapping of a broad range of omic data.It features maps and visualizes interactions between omic data, such as how the circadian metabolome, transcriptome, and proteome operate in concert.With this technology, users can use non-public and public data, per tissue/organ data and data across multiple conditions.

Fluorescent Biosensor for Methyltransferase Assay

Correct epigenetic regulation is essential to cellular development, and methyltransferases are enzymes important for epigenetic regulatory processes. They add methyl groups to their substrates, which can be DNA, proteins, or small-molecule secondary metabolites. Methyltransferases have been implicated in a number of diseases, including cancer, HIV infection, and diabetes, yet many remain uncharacterized.S-adenosyl methionine (SAM) is used as a methyl group donor by a majority of methyltransferases. Use of SAM by a methyltransferase results in the production of S-adenosyl homocysteine (SAH). SAM is found across all branches of life, and therefore represents a useful biological marker for methyltransferase activity. Researchers at UC Berkeley have developed a sensitive and selective means of assaying methyltransferase activity. This assay monitors the presence of SAH, and can be used for high-throughput screening.

Alignment-Free Rapid Sequence Census Quantification (Kallisto)

Sequence census experiments utilize next-generation sequence data to estimate the relative abundance of target sequences.  Since the samples are often short DNA fragments, they must first be assigned to the correct transcripts and genes that produced them, and this alignment or mapping step currently takes up the majority of computing power and time in most expression analyses. To avoid this costly process, UC Berkeley researchers have developed a software program (kallisto) for quantifying abundances of transcripts from RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads based on pseudo-alignment for rapidly determining the compatibility of reads with targets, without the need for alignment. Pseudo-alignment of reads preserves the key information needed for quantification. 

On-Chip Platform for Single-Molecule Electrical Conductance Measurements

Researchers at the University of California, Davis have developed a microchip capable of detecting bacteria and viruses that cause plant and human diseases.

Wireless Remote Sensing of Changes in Fluid Filled Containers

UCLA researchers have developed a novel device and method for continuous and dynamic monitoring of patient fluids that can be used to quickly detect discrepancies suggestive of complications before or after surgery.

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