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“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.

Membrane Insertion of Potential Sensing Nanorods

UCLA researchers in the Department of Chemistry have developed inorganic semiconductor nanosensors that measure membrane voltage.

A Distance-Immune Low-Power Inductively-Coupled Bidirectional Data Link

UCLA researchers in the Department of Electrical Engineering have developed a distance-immune wireless data link for monitoring data in biomedical implants.

Genes, Proteins and Small Molecule Networks Responsible for Neuronal Regeneration

Through integrative analyses of the regeneration-associated gene expression profiling after peripheral nervous system (PNS) injury, combined with multi-level bioinformatics and experimental validation of network predictions, UCLA researchers in the Department of Neurology have identified a small molecule drug that significantly accelerates and improves dorsal root ganglia (DRG) neurite outgrowth in vitro and optic nerve outgrowth in vivo.

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.

Predictive Optimization Of Pharmeceutical Efficacy

UCLA researchers in the Department of Mechanical and Aerospace Engineering have developed a machine learning platform to virtually screen combinatorial drug therapies.

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).

Computational Sensing Using Low-Cost and Mobile Plasmonic Readers Designed by Machine Learning

UCLA researchers have developed a novel method for computational sensing using low-cost and mobile plasmonic readers designed by machine learning.

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.

Immunogenic Peptides as Vaccines against Herpes Simplex Virus

Immunogenic peptides isolated from HSV seropositive asymptomatic (ASYMP) individuals induce a CD8+ T cell- dependent protective immunity against herpes virus in a mammal.


Microinjection represents the “gold standard” for cellular manipulation, due to its precision, safety, and applicability to a wide variety of cell types and molecules.  However, the reliance of current instrumentation on skilled operators and serialized injection methodologies limits availability and throughput (~3 cells/min), thus hampering progress in many areas including ex-vivo cell therapies. Automation efforts have shown promise for improving success rates, but the expense of instrument complexity and limited gains in throughput (≤35 cells/min) have held back its universal adoption.    

Novel and Effective Gene Therapy for Critical Limb Ischemia

Critical limb Ischemia (CLI) represents a significant unmet medical need since there are currently no effective pharmaceuticals or biologic therapies for treatment of patients with occluded vessels. Researchers at the University of California, Davis have designed a Mesenchymal Stem/Stromal Cell (MSC) which secretes supraphysiological amounts of human Vascular Endothelial Growth Factor (VEGF) for revascularization of blood vessels and the treatment of peripheral artery diseases such as CLI.

MEMS Nanowire Ion Sensor

Sensing and quantifying ions in liquid is important in many research and commercial applications. For instance, pH is often a key component in manufacturing. In biology, sensing ions in solution, such as lab-on-a-chip applications, can be pivotal to an effective application. In many of these technology areas, miniaturization and low cost production of ion sensors is critical.To address this challenge, investigators at University of California at Berkeley have developed a MEMS nanowire ion sensor. This sensor employs a MEMS device where ions are sensed with nanowires using an alternating current (AC) electric field. The MEMS nanowire ion sensor can serve as a chemical sensor. By example, the MEMS nanowire ion sensor can be employed as a pH sensor or pH monitor for environment, infrastructure or plant facility. In biologic applications, the MEMS nanowire ion sensor can serve as a biosensor for biomolecule detection, DNA sequences, blood testing, and an ion species identifier, among others. 

DNA Sequence Assembly Software (Design Evolver)

DNA sequence assembly software is used for designing the construction of longer DNA molecules from fragments of shorter DNA molecules. Current methods of sequence assembly are expensive, slow and prone to failure. Investigators at UC Berkeley have developed a sequence assembly tool, Design Evolver, which is cheaper, faster, easier to implement and less prone to failure than alternate tools. The software works in conjunction with the j5 DNA assembly tool developed and licensed by the Joint BioEnergy Institute (JBEI). Design Evolver’s algorithm can further optimize designs that have been processed by j5.

System And Method For Capturing Vital Vascular Fingerprint

Improved reliability of fingerprint authentication is achieved through a unique vascular fingerprint which increases accuracy and verifies liveness.

Inclined Single Plane Imaging Microscope Box (iSPIM Box)

Researchers at University of California, Irvine, have responded to the worldwide growing demand for fast 3D microscopy in bioimaging, by creating iSPIM Box (Inclined Single Plane Imaging Microscope Box), an adapter for commercial body microscopes, which can be used to achieve high spatial and temporal resolution in live cell imaging with only simple sample preparation in common culture dishes.

Statistical Comparison of Rank Lists and Molecular Profiles

The RRHO algorithm allows for the comparison of two gene expression signatures. Each signature is processed as a ranked list based on expression differences between two classes of samples. The signatures can be input either as raw expression data and sample and class labels, or as a pre-ranked gene list. 

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