JIMB’s research projects answer the biotechnology industry’s calls for measurement tools. The following are a few examples.


 
 

Erin Mitsunaga
Ph. D. Candidate, Stanford Genetics

Our immune systems mount intricate responses to infection and disease, keeping us healthy. Ms. Mitsunaga is developing new methods for decoding complicated & dynamic immune responses.


 
 

Dr. Noah Spies
Postdoctoral Researcher, Stanford School of Medicine
Geneticist, California NIST Team, Genome-Scale Measurements

DNA Sequencing is a powerful tool for learning how normal cells become cancerous. However, the affordability and reliability of DNA-based measurements needs improving. Dr. Spies is figuring this out.


 
 

Dr. Sarah Munro
Leader, California NIST Team, Genome-Scale Measurements
Visiting Stanford Scholar

Can you trust your genome-scale measurements of RNA? Dr. Munro develops RNA controls and analysis software to provide confidence in gene expression experiments.


 
 

Dr. Ariel Hecht
Bioengineer, California NIST Team, Genome-Scale Measurements
Visiting Stanford Scholar

Qualifying protein expression in living cells is difficult. Dr. Hecht is developing a new protein expression measurement technique that uses a fluorescent protein as a reference to indirectly measure the expression of a non-fluorescent protein.


Dr. Julia Salzman
Assistant Professor of Biochemistry and of Biomedical Data Science

Our textbooks teach us that our DNA is read into one set of instructions for the cell. Computational analysis revealed that there are messages made by cells that were missed for decades.  If we can use statistics to accurately detect all the messages in a cell, we might be able to have better and earlier ways of
detecting diseases.


 
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Fengjiao Lyu
Ph.D. Candidate, Mechanical Engineering, Stanford University

More than 700,000 deaths are attributable to antibiotic resistance every year. One solution CDC proposed is rapid and strong detection. Ms. Lyu is working on a rapid and accurate detection method using droplet-based microfluidics.


 
 

Dr. Lars Steinmetz
Genetics Professor, Stanford University

What if we could assess the functional impact of every position in the genome?  To realize this potential, the Steinmetz laboratory is developing technology to edit thousands of genomic sites in parallel. In the process they are establishing rules for how to engineer precise genome modifications with RNA-guided nucleases and host-cell DNA without unintended off-target effects.


 
 

Dr. Polly Fordyce
Assistant Professor, Departments of Genetics and Bioengineering

Current attempts to design novel enzymes with industrial or therapeutic applications rely on random chance to identify efficient candidates. Could we rationally design more efficient enzymes if we better understood how they position active site residues for catalysis?


 
 

Aaron Mitchell
Ph.D. Candidate, Bioengineering, Stanford University

Overexpression and dysregulated activity of enzymes called proteases leads to more aggressive cancers.  Mr. Mitchell is engineering a highly potent inhibitor targeted to shut down protease activity and effectively halt cancer progression. Efforts are also being made to develop a novel high throughput screening technology for rapid protease inhibitor drug discovery.


 
 

Calvin Schmidt
Ph.D. Candidate, Bioengineering, Stanford University

Mr. Schmidt is building computational tools that make the engineering of biology easier. The tools are automated structural analysis and machine learning to predict the activity of functional RNA devices for use as genetic switches. 


 
 

Dr. Rhiju Das
Computational Biochemist, Associate Professor, Stanford University School of Medicine

Dr. William Greenleaf
Assistant Professor, Genetics, Stanford University

Rational engineering of RNA molecules that switch on and off genes could revolutionize medicine. But RNA computer-assisted design is error-prone due to radically incomplete measurements of the stability of RNA modules. Dr. Das and Dr. Greenleaf are working to measure them all.


 
 

Cameron Prybol
Ph.D. Candidate, Genetics, Stanford University School of Medicine

RNA predated DNA and proteins in the formation of life on Earth, and RNA continues to play essential roles in all aspects of human biology and disease. Mr. Prybol's research focuses on RNA-mechanisms of gene regulation in the heart, as well as methods that make it easier to work with and learn from RNA data.


 
 

Dr. Nick Melosh
Associate Professor of Materials Science and Engineering
and of Photon Science, Stanford University

There are typically two options to measure a cell: add something to the cell or break the cell open and study its insides on a machine. What if we could use nanostraws to allow for tiny non-destructive sips to be measured?


 
 

Dr. Chaitan Khosla
Professor, School of Chemical Engineering, Stanford University

What we eat combined with our body's health can change the molecular composition of urine, but how such changes are related to specific health conditions are not fully understood. What if, for example, we could simply detect gluten intolerant individuals?


 
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Michael Joseph Sikora
Ph. D. Candidate, Genetics, Stanford University School of Medicine

The recent rapid decrease in cost and increase in sensitivity of sequencing RNA allows for measurement of the dynamic processes that regulate cellular output. Using these methods on cells from various conditions, and even on single cells, we can precisely identify the factors contributing to fundamental phenotypes of the cell regulatory process.


 
 

Nathan Kipniss
Ph.D. Candidate, Bioengineering, Stanford University

CRISPR has revolutionized programmable genome engineering and regulation. Mr. Kipniss is expanding CRISPR based tools for synthetic biology to create synthetic circuits in both prokaryotic and eukaryotic systems.