Philip C. Nelson, Biological Physics, University of Pennsylvania

About Me

I am a physicist.
Some of what I know about science is in my first book. Some more can be found in my second book. Then I learned some more things.
Some of what I know about computers is in my little book. Some more can be found in my little free book.
I teach some courses. One of them is about Electrodynamics (if it doesn't work with Safari, try another browser).
I'm also interested in K-12 education.
See our group's homepage.
Here is my boring official home page and my CV.
I'm a member of Penn's Applied Math and Computational Science Graduate Group.
I was recently Chair of the American Physical Society's Division of Biological Physics. I serve on the editorial board of The Biophysicist journal.

My Books

Latest

Physical Models of Living Systems

Second ed., revised, clarified, updated, and enlarged (Chiliagon Science, 2022). Available as an e-book from Amazon. For a hard copy, check this link. The new edition is available in Chinese translation: 生命系统的物理建模（第二版） at these two links.

Responses to the new edition:

"What I find special about this book is its elegance in transitioning from fundamental math to applications in biology and the analysis of real-world data. The book chapters integrate together beautifully and the problem sets are a rare asset." -- Prof. Amir Erez, Hebrew University

"An excellent book, well written and beautifully illustrated.... Lots of homework problems, comparisons to real data, and a winning combination of words, pictures, equations, and computer code... a masterpiece." -- Prof. Bradley Roth, Univ. of Oakland

"A wonderful textbook. It stretches life science students to not only see but also understand how randomness at the heart of living systems can lead to predictable outcomes. Students in my class, taught using PMLS, found the text to be intellectually challenging and, as a result, interesting and memorable." -- Prof. Douglas Martin, Lawrence University

Reviews of the first edition:

"Particularly compelling for its smooth integration of biological experiments, physical models, and computational exercises. Readers who complete the text will be well equipped with the computational and mathematical skills needed for a quantitative understanding of a range of biological systems.... Thanks to Nelson's skillful writing and the excellent accompanying online resources, this book will appeal to a broad audience and teach even a beginner how to solve problems numerically." -- Eva-Maria Collins in Physics Today

"Philip Nelson has done a terrific job.... There are numerous traits that make this text unique among the very many books of biological physics.... The presentation of materials is developed in an innovative fashion.... There is a nice balance between conceptual examples and end-of-the-chapter problems.... Physical Models of Living Systems.... will benefit undergraduates as well as others with clear interests in genomics, proteomics, cellular signaling, bioengineering, regenerative medicine, and synthetic biology." -- Liviu Movileanu in American Journal of Physics 84 (6), June 2016

"[T]his excellent book will appeal to both students and professional scientists in the field of quantitative biology.... [T]he book feels personal in its selection of topics and the training journey on which it takes its readership. In our opinion, the combination of this uniqueness with technical accuracy makes the book a noteworthy and valuable addition to resources for advanced biophysics education... [T]he book conveys rich information, is clearly structured, and provides comprehensive data sets... Nelson shows how computational programming can be used effectively in modeling biological systems at the cellular and molecular levels." -- Dietlind L. Gerloff and Jonghoon Kang. Cell Biology Education (2016) vol. 15 (4) pp. fe11-fe11.

Student's Guide to Python for Physical Modeling, Second Edition

(with Jesse M. Kinder) (Princeton Univ. Press, 2021; ISBN: 9780691223650). You can get from Princeton. E-book editions are available from Amazon and other distributors. For price comparisons see nicebooks.

Besides many clarifications and updates, this new edition adds sections on elementary data science, pandas, version control, and user-defined classes. As with the first edition, however, our aim remains for the main text to be short, basic, and suitable for science students, even those who have never programmed before. A student who spends a week working through this book will get many basic skills that we as scientists use constantly, with the free and open-source Python platform that is becoming the computing environment of choice for many.

The book has an associated blog. Chapter 1 is freely available. A Chinese-language translation of the first edition is available (Python物理建模初学者指南（第2版）), and also a Korean-language edition.

"An excellent stepping stone into the world of using Python in computational science... After working through the chapters and their accompanying exercises, readers can expect not only to know how to write and read Python but also to achieve a thorough understanding for developing complex physical models and calculations." - Kevin Thielen and Vivienne Tien in "Computing in Science & Engineering" May/June 2016

Recent

Biological Physics Student Edition: Energy, Information, Life

Revised, clarified, and updated (Chiliagon Science, 2022). Contents and prefaces are here. Chapter 1 is freely available.

The e-book is available for $9.99 from Amazon. Its ISBN number is 978-0-578-69547-1.

The paperback book is available for suggested retail $29.00 from the usual online retailers. University bookstores and libraries can get it from Ingram using its ISBN number: 978-0-578-68702-5.

"This clear and well-structured text emphasizes the connections between statistical mechanics and biophysical phenomena." -- R. Parthasarathy, in Am. J. Physics 2021

The new edition is available in translation: 生物物理学（第二版）at these two links.

"This book inspired me to write [my] book in the first place. Biological Physics is the most interesting and well-written textbook I have ever read." -- Peter M. Hoffman, Life's Ratchet

Recent

From Photon to Neuron: Light, Imaging, Vision

(Princeton Univ. Press, 2017). The hard copy edition is available from Princeton. There is an e-book edition, available for Kindle or via Google Play. The Contents, "To the Student," and "To the Instructor" are freely available here as well as Chapter 1. Three additional chapters are freely available in preliminary form.

A Chinese language translation is available: 从光子到神经元：光、成像、视觉.

"From Photon to Neuron: Light, Imaging, Vision completes a trilogy begun by Biological Physics and Physical Models of Living Systems. Those works establish Nelson as the preeminent author of textbooks at the intersection of physics and biology... Nelson uses words, pictures, formulas, and code to teach students how to construct models and interpret data. His books provide a master class in how to integrate those four different approaches into a complete learning experience." -- Brad Roth, in Physics Today magazine

"A thorough and sweeping tour from the fundamental physics of light to the neurobiology of the retina... Lavishly illustrated and carefully explained." -- Sönke Johnsen, Biology, Duke University, in American Journal of Physics

"As elegant as it is deep. A masterful tour of the science of light and vision, it goes beyond artificial boundaries between disciplines and presents all aspects of light as it appears in physics, chemistry, biology and the neural sciences... One of the most insightful, cross-disciplinary texts I have read in many years. It is mesmerising and will become a landmark in rigorous, but highly accessible interdisciplinary literature." -- Luis Alvarez-Gaumé, Stony Brook University, in CERN Courier

Student's Guide to MATLAB for Physical Modeling

(With Tom Dodson; free).

In Plain English

Plain-English Videos

"Why are there so many songs about rainbows?" (Penn Science Cafe, 9/2023).
"Effects of Greenhouse Gases on Earth, Venus, and Mars" (Shaw-IAU Workshop on Astronomy for Education, 11/2023).
Intro to my talk on "Learning Biophysics via Modeling and Simulation: a Course for Science and Engineering Undergraduates." (2023 Biophysical Society meeting).
How to solve equations you didn't think you could solve (and model a pandemic) (Improved edition, Summer 2022, Penn EPRA).
Physics of human and superhuman vision (the A. O. Williams Lecture, Brown University, 2018) Also available on iTunesU.

the slides

Bill Berner's Physics demo shows! Get them via iTunesU or via vimeo. And here are some spiffy ones.
An object that mimics gravitational lensing.
Double refraction in a calcite crystal.
Effect of temperature on conductivity of a metal.
Rayleigh scattering from a colloidal suspension.
Laboratory rainbow.
Faraday's magneto-optical effect.
Interference vs polarization.
Optical rotatory power of sugar solution.
The infrared activity of carbon dioxide gas.
Thermal properties of soft matter.
Diamagnetic Levitation.
Microwaves versus light.
Magnetoelectrophoresis starring Mary Marcopul.
And get out your hankerchief as you watch Langmuir's home movies from Solvay 1927. (Look for a playful Marie Curie.)

Plain-English Articles

Attention, Intentions, and Just Plain Tension, University of Pennsylvania Almanac 67:11 (2020).
A Demonstration of the Infrared Activity of Carbon Dioxide Gas. Physics Teacher (April 2019).
Time to Stop Telling Biophysics Students that Light is Primarily a Wave. Biophys. J. 114, 761-765 (2018).
Coding and Data Visualization in the Science Classroom, University of Pennsylvania Almanac 63:6 (2016).

Slides and Videos from Recent Talks

Loved into Being: Tom McLeish's love of scientific meaning, and the scientific meaning of love "Celebrating Tom McLeish," Durham 9/2024).
How physicists get started thinking about new phenomena (SEMF conference July 2024).
Workshop on scientific animation in Python (UQ-Bio conference 6/2024).
Single-molecule evidence for a new proofreading step in ribosome (APS March Meeting 2024).
Inference in Biological Physics (Syracuse University, 1/2024).
Effects of greenhouse gases on Earth, Venus & Mars (Shaw-IAU workshop)
"Bonds, Catch Bonds, and Statistics" (APS March Meeting 2021). Poster at 2021 Biophysical Society Meeting. And here is the book chapter on which it was based.
"How could anything like that possibly happen at all?" Getting and sustaining attention from demo, through analysis, to tech payoff. From the Communicating biological physics tutorial at 2023 APS March Meeting.
Learning Biological Physics via Modeling and Simulation, 2023 Biophysical Society meeting.
A Tutorial Model for the Role of Superspreaders in Pandemic Outbreaks, short talk at the 2022 APS March meeting. (Video may not play in Safari.)
My poster at the 2022 APS March meeting on "Learning Biophysics via Modeling and Simulation: a Course for Science and Engineering Undergraduates."
The intrinsic allure of extrinsic curvature (The Rouse Ball Lecture, Univ. of Cambridge, 2019). Here's a video of the talk (Univ. Pennsylvania, 2020).
The Physics, Biology, and Technology of Resonance Energy Transfer (Rutgers Stat Mech Conference, 2019).
Gene Expression, Kinetic Proofreading, and Stochastic Simulation (Marine Biology Lab, Woods Hole, 8/2018).
Planetary Physiology (Marine Biology Laboratory, 8/2018).
Activities and Classroom Demonstrations in Biological Physics, a workshop at American Association of Physics Teachers (7/2018). And here are detailed notes including recipes to perform the demos in that workshop.

Journal Publications

Most of these articles are freely available at Penn's Scholarly Commons (if it doesn't work with Safari, try another browser).

Here are my profiles in ResearcherID, ORCID, Scopus, and Google Scholar.

The research in these publications was funded in part by The National Science Foundation and by the Human Frontier Science Program. "Any opinions, findings, confusions, contusions, contortions, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation."

Note: PDF reprints are provided below within the context of fair use.
What gives the great accuracy observed in gene translation?
Single-Molecule Studies of Cognate and Near-Cognate Elongation in an in vitro Eukaryotic Translation System. With Fritsch, Bhattacharya, Ng, Li, Cooperman, Goldman. bioRxiv 2024.08.29.609187.
In the CO2 absorption bands the atmosphere is already completely opaque, and you can't exceed 100% absorption, so how can adding more hurt?
Effects of Greenhouse Gases on Earth, Venus, and Mars: Beyond the One-Blanket Model. Am. J. Phys. 91, 721--730 (2023).
How can cellular recognition processes be so accurate?
Stochastic Simulation to Visualize Gene Expression and Error Correction in Living Cells. With Chen and Zuckerman. The Biophysicist 1(1), Article_1 (14 pages) (2020).
How can a system behave in a way that is strongly classical yet also strongly quantum?
The Role of Quantum Decoherence in FRET. Biophys. J. 115 167--172 (2018).
Does the quantum character of light matter for our eyes?
Old and New Results About Single-photon Sensitivity in Human Vision. Physical Biology 13 025001 (2016).
Does a molecular motor pause to search for its next stepping spot?
Tilting and Wobble of Myosin V by High-speed Single-molecule Polarized Fluorescence Microscopy. With Beausang, Schroder, and Goldman. Biophysical Journal 104 1263--1273 (2013). (featured in BJ's "Best of 2013"
How does a wave of cell division spread across an embryo?
Wavefront Propagation and Mechanical Signaling in Early Drosophila Embryos . With Idema, Dubuis, Kang, Manning, Lubensky, and Liu. PLoS ONE 8 e77216 (2013).
How much data compression is occurring in your retina?
Retinal Adaptation to Spatial Correlations. With Simmons, Prentice, Tkacik, Homann, Yee, Palmer, and Balasubramanian. PLoS Computational Biology 9 e1003344 (2013).
What is each retinal ganglion cell looking for?
Neural Spikes, Identification from a Multielectrode Array. With Prentice, Homann, Simmons, Tkacik, Balasubramanian. Encyclopedia of Applied and Computational Mathematics, in press.
How precisely can you pinpoint a rate change?
Changepoint Analysis for Single-molecule Polarized Total Internal Reflection Fluorescence Microscopy Experiments. With Beausang and Goldman. Methods Enzymol. 487 431-463 (2011)..
When we eavesdrop on a retina, who said what when?
Fast, Scalable, Bayesian Spike Identification for Multi-electrode Arrays. With Prentice, Homann, Simmons, Tkacik, and Balasubramanian. PLoS ONE 6(7): e19884.
How should you design the right DNA to make the best measurements of looping?
Calibration of Tethered Particle Motion Experiments. With Han, Lui, Blumberg, Beausang, and Phillips.In Mathematics of DNA Structure, Function and Interactions, eds. C.J. Benham et al. (Springer, 2009).
How can we monitor gene-regulatory events without any cells?
Concentration and Length Dependence of DNA Looping. With Han, Garcia, Blumberg, Towles, Beausang, and Phillips. PLoS ONE, 4 e5621 (2009).
Does myosin twist the `wrong' way around actin as it walks?
Twirling of Actin by Myosins II and V Observed via Polarized TIRF in a Modified Gliding Assay. With Beausang, Schroeder, and Goldman. Biophys J. 95 5820 (2008).
Is there spooky action at a distance in living cells?
The Role of Microtubule Movement in Bidirectional Organelle Transport. With Kulic, Brown, Kim, Kural, Blehm, Selvin, and Gelfand. PNAS 105 10011 (2008). (See also the amazing movies.)
How does a regulatory protein manage to grab two distant places on a strand of DNA?
First-principles Calculation of DNA Looping in Tethered Particle Experiments, final version, and its supplement. With Towles, Beausang, Garcia, and Phillips. Physical Biology, 6 025001 (2009).