About

Jan Liphardt is an Associate Professor of Bioengineering at Stanford University. He is based at the Shriram Center in Stanford, California. His research focuses on bioengineering, and he is involved in various research areas, including translational research and collaborative projects within Stanford's bioengineering community. Further details about his specific research contributions or background are not provided on the page.

Research topics

• Artificial Intelligence
• Computer Science
• Cell biology
• Cancer research
• Internal medicine
• Pathology
• Biology
• Physics
• Computer vision
• Medicine
• Endocrinology

Selected publications

• Robust fluorescent labeling and tracking of endogenous non-repetitive genomic loci

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-08-27 · 2 citations

  preprintOpen access

  Abstract The spatial organization and dynamics of a genome are central to gene regulation. While a comprehensive understanding of chromatin organization in the human nucleus has been achieved using fixed-cell methods, measuring the dynamics of specific genomic regions over extended periods in individual living cells remains challenging. Here, we present a robust and fully genetically encoded system for fluorescent labeling and long-term tracking of any accessible non-repetitive genomic locus in live human cells using fluorogenic and replenishable nanobody array fusions of the Staphylococcus aureus dCas9, and compact polycistronic single guide (sg)RNAs. First, we characterize the selectivity and photostability of our probes, enabling genome-wide visualization of chromatin dynamics at locally repetitive elements. Next, through multiplexed expression of 8–10 sgRNAs from polycistronic cassettes, we demonstrate efficient and sustained labeling of non-repetitive loci, enabling high-fidelity tracking of gene-proximal regions at exceptional spatial and temporal resolution. Finally, by correlating chromatin mobility with transcriptional activity at multiple genes, we find that local chromatin dynamics at 20 Hz are gene-specific and not necessarily dependent on transcription. Our approach is versatile, minimally invasive, and scalable, enabling multiplexed imaging of regulatory element dynamics involved in gene control, with broad applicability across diverse biological systems and disease contexts.

  PublisherOA PDFDOI

• On Stress: Combining Human Factors and Biosignals to Inform the Placement and Design of a Skin-like Stress Sensor

  2024-05-11 · 7 citations

  articleOpen access

  With advances in electronic-skin and wearable technologies, it is possible to continuously measure stress markers from the skin and sweat to monitor and improve wellbeing and health. Understandably, the sensor’s engineering and resolution are important towards its function. However, we find that people looking for an e-skin stress sensor may look beyond measurement precision, demanding a private and stealth design to reduce, for example, social stigmatization. We introduce the idea of a stress sensing "wear index," created from the combination of human-centered design (n=24), physiological (n=10), and biochemical (n=16) data. This wear index can inform the design of stress wearables to fit specific applications, e.g., human factors may be relevant for a wellbeing application, versus a relapse prevention application that may require more sensing precision. Our wear index idea can be further generalized as a method to close gaps between design and engineering practices.

  PublisherOA PDFDOI

• A Paragraph is All It Takes: Rich Robot Behaviors from Interacting, Trusted LLMs

  arXiv (Cornell University) · 2024-12-24

  preprintOpen accessSenior author

  Large Language Models (LLMs) are compact representations of all public knowledge of our physical environment and animal and human behaviors. The application of LLMs to robotics may offer a path to highly capable robots that perform well across most human tasks with limited or even zero tuning. Aside from increasingly sophisticated reasoning and task planning, networks of (suitably designed) LLMs offer ease of upgrading capabilities and allow humans to directly observe the robot's thinking. Here we explore the advantages, limitations, and particularities of using LLMs to control physical robots. The basic system consists of four LLMs communicating via a human language data bus implemented via web sockets and ROS2 message passing. Surprisingly, rich robot behaviors and good performance across different tasks could be achieved despite the robot's data fusion cycle running at only 1Hz and the central data bus running at the extremely limited rates of the human brain, of around 40 bits/s. The use of natural language for inter-LLM communication allowed the robot's reasoning and decision making to be directly observed by humans and made it trivial to bias the system's behavior with sets of rules written in plain English. These rules were immutably written into Ethereum, a global, public, and censorship resistant Turing-complete computer. We suggest that by using natural language as the data bus among interacting AIs, and immutable public ledgers to store behavior constraints, it is possible to build robots that combine unexpectedly rich performance, upgradability, and durable alignment with humans.

  PublisherOA PDFDOI

• Data from A Mutation in Histone H2B Represents a New Class of Oncogenic Driver

  2023-04-03

  preprintOpen access

  <div>Abstract<p>By examination of the cancer genomics database, we identified a new set of mutations in core histones that frequently recur in cancer patient samples and are predicted to disrupt nucleosome stability. In support of this idea, we characterized a glutamate to lysine mutation of histone H2B at amino acid 76 (H2B-E76K), found particularly in bladder and head and neck cancers, that disrupts the interaction between H2B and H4. Although H2B-E76K forms dimers with H2A, it does not form stable histone octamers with H3 and H4 <i>in vitro,</i> and when reconstituted with DNA forms unstable nucleosomes with increased sensitivity to nuclease. Expression of the equivalent H2B mutant in yeast restricted growth at high temperature and led to defective nucleosome-mediated gene repression. Significantly, H2B-E76K expression in the normal mammary epithelial cell line MCF10A increased cellular proliferation, cooperated with mutant <i>PIK3CA</i> to promote colony formation, and caused a significant drift in gene expression and fundamental changes in chromatin accessibility, particularly at gene regulatory elements. Taken together, these data demonstrate that mutations in the globular domains of core histones may give rise to an oncogenic program due to nucleosome dysfunction and deregulation of gene expression.</p>Significance:<p>Mutations in the core histones frequently occur in cancer and represent a new mechanism of epigenetic dysfunction that involves destabilization of the nucleosome, deregulation of chromatin accessibility, and alteration of gene expression to drive cellular transformation.</p><p><i>See related commentary by Sarthy and Henikoff, p. 1346</i>.</p><p><i>This article is highlighted in the In This Issue feature, p. 1325</i></p></div>

  PublisherDOI

• Supplemental Text and Figures from A Mutation in Histone H2B Represents a New Class of Oncogenic Driver

  2023-04-03

  preprintOpen access

  <p>Supplemental materials and methods and Supplemental Figures 1-7</p>

  PublisherDOI

• Supplementary Table 3: H3 from A Mutation in Histone H2B Represents a New Class of Oncogenic Driver

  2023-04-03

  supplementary-materialsOpen access

  <p>List of all H3 missense mutations in cBioPortal and dbSNP analysis</p>

  PublisherDOI

• Supplementary Table 1: H2A from A Mutation in Histone H2B Represents a New Class of Oncogenic Driver

  2023-04-03

  supplementary-materialsOpen access

  <p>List of all H2A missense mutations in cBioPortal and dbSNP analysis</p>

  PublisherDOI

• Supplementary Table 4: H4 from A Mutation in Histone H2B Represents a New Class of Oncogenic Driver

  2023-04-03

  supplementary-materialsOpen access

  <p>List of all H4 missense mutations in cBioPortal nad dbSNP analysis</p>

  PublisherDOI

• Supplementary Table 1: H2A from A Mutation in Histone H2B Represents a New Class of Oncogenic Driver

  2023-04-03

  supplementary-materialsOpen access

  <p>List of all H2A missense mutations in cBioPortal and dbSNP analysis</p>

  PublisherDOI

• Data from A Mutation in Histone H2B Represents a New Class of Oncogenic Driver

  2023-04-03

  preprintOpen access

  <div>Abstract<p>By examination of the cancer genomics database, we identified a new set of mutations in core histones that frequently recur in cancer patient samples and are predicted to disrupt nucleosome stability. In support of this idea, we characterized a glutamate to lysine mutation of histone H2B at amino acid 76 (H2B-E76K), found particularly in bladder and head and neck cancers, that disrupts the interaction between H2B and H4. Although H2B-E76K forms dimers with H2A, it does not form stable histone octamers with H3 and H4 <i>in vitro,</i> and when reconstituted with DNA forms unstable nucleosomes with increased sensitivity to nuclease. Expression of the equivalent H2B mutant in yeast restricted growth at high temperature and led to defective nucleosome-mediated gene repression. Significantly, H2B-E76K expression in the normal mammary epithelial cell line MCF10A increased cellular proliferation, cooperated with mutant <i>PIK3CA</i> to promote colony formation, and caused a significant drift in gene expression and fundamental changes in chromatin accessibility, particularly at gene regulatory elements. Taken together, these data demonstrate that mutations in the globular domains of core histones may give rise to an oncogenic program due to nucleosome dysfunction and deregulation of gene expression.</p>Significance:<p>Mutations in the core histones frequently occur in cancer and represent a new mechanism of epigenetic dysfunction that involves destabilization of the nucleosome, deregulation of chromatin accessibility, and alteration of gene expression to drive cellular transformation.</p><p><i>See related commentary by Sarthy and Henikoff, p. 1346</i>.</p><p><i>This article is highlighted in the In This Issue feature, p. 1325</i></p></div>

  PublisherDOI

Recent grants

• NIH Grant R01GM077856

  NIH · $1.6M · 2014

• NIH Grant R01GM084716

  NIH · $495k · 2011

• In vitro and in vivo Single Molecular Experiments of Biological Systems

  NSF · $1.5M · 2007–2013

• NIH Grant U54CA143836

  NIH · $6.0M · 2015

• NIH Grant U01EB021237

  NIH · $1.1M · 2018

Frequent coauthors

• Quanming Shi

  Stanford University

  48 shared

• Rajarshi P. Ghosh

  Howard Hughes Medical Institute

  42 shared

• Carlos Bustamante

  University of California, Berkeley

  38 shared

• Valerie M. Weaver

  University of California, San Francisco

  30 shared

• Eliane Trepagnier

  28 shared

• J. Matthew Franklin

  Stanford University

  20 shared

• Gavin E. Crooks

  20 shared

• Félix Ritort

  Universitat de Barcelona

  17 shared

Education

• Ph.D., Bioengineering

  Stanford University

  2000

• B.S., Bioengineering

  University of California, Berkeley

  1995