Cited by 4Philosophy of Biology and Scientific ExplanationMicrotubule and mitosis dynamicsAdvanced Thermodynamics and Statistical Mechanics

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Biological processes as exploratory dynamics

Open access
Kondev, Jane, Kirschner, Marc, Garcia, Hernan G., Salmon, Gabriel L., Phillips, Rob·2026·Biophysical Journal

Published version of a preprint

Abstract

Many biological processes can be thought of as the result of an underlying dynamics in which the system repeatedly undergoes distinct and abortive trajectories with the dynamical process only ending when some specific process, purpose, structure, or function is achieved. A classic example is the way in which microtubules attach to kinetochores as a prerequisite for chromosome segregation and cell division. In this example, the dynamics is characterized by apparently futile time histories in which microtubules repeatedly grow and shrink without chromosomal attachment. We hypothesize that for biological processes for which it is not the initial conditions that matter, but rather the final state, this kind of exploratory dynamics is biology's unique and necessary solution to achieving these functions with high fidelity. This kind of cause-and-effect relationship can be contrasted to examples from physics and chemistry where the initial conditions determine the outcome. In this paper, we examine the similarities of many biological processes that depend upon random trajectories starting from the initial state and the selection of subsets of these trajectories to achieve some desired functional final state. We begin by reviewing the long history of the principles of dynamics, first in the context of physics, and then in the context of the study of life. These ideas are then stacked up against the broad categories of biological phenomenology that exhibit exploratory dynamics. We then build on earlier work by making a quantitative examination of a succession of increasingly sophisticated models for exploratory dynamics, all of which share the common feature of being a series of repeated trials that ultimately end in a "winning" trajectory. We also explore the ways in which microscopic parameters can be tuned to alter exploratory dynamics as well as the energetic burden of performing such processes. It is a great privilege to take part in this special volume dedicated to the life and work of Prof. Erich Sackmann (1934-2024). For one of us (R.P.), at the time of making a switch from traditional condensed matter physics to a life engaged in the study of life, he went to a meeting near Munich that completely opened his eyes to the ways in which the approach of physics could be brought to bear on the study of the living. Sackmann's work was an inspiring presence at that meeting. One of the hallmarks of his work was a principled approach to dissecting biological processes over a range of scales and phenomena. One common thread to much of his work was that it acknowledged the dynamical character of living organisms. The present paper attempts to follow in the tradition of Sackmann's studies of dynamics by suggesting a new way of looking at many biological processes all through the unifying perspective of what we will call exploratory dynamics.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.bpj.2025.09.009

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 59

  1. Klein, 1973, Mechanical Explanation at the End of the Nineteenth Century, Centaurus, 17, 58, 10.1111/j.1600-0498.1973.tb00184.x · DOI
  2. Richter, 1986, Kelvin and the Age of the Earth, J. Geol., 94, 395, 10.1086/629037 · DOI
  3. Chandrasekhar, 1943, Stochastic problems in physics and astronomy, Rev. Mod. Phys., 15, 1, 10.1103/RevModPhys.15.1 · DOI
  4. Kirschner, 1986, Beyond Self-Assembly - from Microtubules to Morphogenesis, Cell, 45, 329, 10.1016/0092-8674(86)90318-1 · DOI
  5. Winter, 1981, Diffusion-driven mechanisms of protein translocation on nucleic acids. 2. The Escherichia coli repressor–operator interaction: equilibrium measurements, Biochemistry, 20, 6948, 10.1021/bi00527a029 · DOI
  6. Winter, 1981, Diffusion-driven mechanisms of protein translocation on nucleic acids. 3. The Escherichia coli lac repressor–operator interaction: kinetic measurements and conclusions, Biochemistry, 20, 6961, 10.1021/bi00527a030 · DOI
  7. Hu, 2006, How proteins search for their specific sites on DNA: the role of DNA conformation, Biophys. J., 90, 2731, 10.1529/biophysj.105.078162 · DOI
  8. Hachmo, 2023, Conditional probability as found in nature: Facilitated diffusion, Am. J. Phys., 91, 653, 10.1119/5.0123866 · DOI
  9. Mitchison, 1985, Properties of the Kinetochore In vitro. II. Microtubule Capture and ATP-Dependent Translocation, J. Cell Biol., 101, 766, 10.1083/jcb.101.3.766 · DOI
  10. Holy, 1994, Dynamic Instability of Microtubules as an Efficient Way to Search in-Space, Proc. Natl. Acad. Sci. USA, 91, 5682, 10.1073/pnas.91.12.5682 · DOI
  11. Gundersen, 2002, Evolutionary conservation of microtubule-capture mechanisms, Nat. Rev. Mol. Cell Biol., 3, 296, 10.1038/nrm777 · DOI
  12. Wollman, 2005, Efficient chromosome capture requires a bias in the ‘search-and-capture’ process during mitotic-spindle assembly, Curr. Biol., 15, 828, 10.1016/j.cub.2005.03.019 · DOI
  13. Heald, 2015, Thirty years of search and capture: The complex simplicity of mitotic spindle assembly, J. Cell Biol., 211, 1103, 10.1083/jcb.201510015 · DOI
  14. Ghabrial, 2003, Branching morphogenesis of the tracheal system, Annu. Rev. Cell Dev. Biol., 19, 623, 10.1146/annurev.cellbio.19.031403.160043 · DOI
  15. Li, 2021, Cellular bases of olfactory circuit assembly revealed by systematic time-lapse imaging, Cell, 184, 5107, 10.1016/j.cell.2021.08.030 · DOI
  16. Tonegawa, 1983, Somatic generation of antibody diversity, Nature, 302, 575, 10.1038/302575a0 · DOI · Paper page
  17. Prince, 1992, Satellite Tracking of Wandering Albatrosses (Diomedea-Exulans) in the South-Atlantic, Antarct. Sci., 4, 31, 10.1017/S0954102092000075 · DOI
  18. Block, 2011, Tracking apex marine predator movements in a dynamic ocean, Nature, 475, 86, 10.1038/nature10082 · DOI
  19. Kays, 2015, Terrestrial animal tracking as an eye on life and planet, Science, 348, 10.1126/science.aaa2478 · DOI · Paper page
  20. Antolos, 2017, Foraging Behavior and Energetics of Albatrosses in Contrasting Breeding Environments, Front. Mar. Sci., 4, 10.3389/fmars.2017.00414 · DOI
  21. Hindell, 2020, Tracking of marine predators to protect Southern Ocean ecosystems, Nature, 580, 87, 10.1038/s41586-020-2126-y · DOI
  22. Hopfield, 1974, Kinetic proofreading: A new mechanism for reducing errors in biosynthetic processes requiring high specificity, Proc. Natl. Acad. Sci. USA, 71, 4135, 10.1073/pnas.71.10.4135 · DOI · Paper page
  23. Ninio, 1975, Kinetic amplification of enzyme discrimination, Biochimie, 57, 587, 10.1016/S0300-9084(75)80139-8 · DOI
  24. Hannezo, 2019, Multiscale dynamics of branching morphogenesis, Curr. Opin. Cell Biol., 60, 99, 10.1016/j.ceb.2019.04.008 · DOI
  25. Palavalli, 2021, Deterministic and Stochastic Rules of Branching Govern Dendrite Morphogenesis of Sensory Neurons, Curr. Biol., 31, 459, 10.1016/j.cub.2020.10.054 · DOI
  26. Bressloff, 2020, Queueing theory of search processes with stochastic resetting, Phys. Rev. E, 102
  27. Evans, 2020, Stochastic resetting and applications, J. Phys. Math., 53
  28. Loisy, 2022, Searching for a source without gradients: How good is infotaxis and how to beat it, Proc. R. Soc. A A., 478
  29. Monthiller, 2022, Surfing on Turbulence: A Strategy for Planktonic Navigation, Phys. Rev. Lett., 129, 10.1103/PhysRevLett.129.064502 · DOI · Paper page
  30. Luby, 1993, Optimal speedup of las vegas algorithms, Inf. Process. Lett., 47, 173, 10.1016/0020-0190(93)90029-9 · DOI
  31. Lacroix, 2022, Spatial and temporal scaling of microtubules and mitotic spindles, Cells, 11, 10.3390/cells11020248 · DOI
  32. Ha, 2024, Measuring and modeling the dynamics of mitotic error correction, Proc. Natl. Acad. Sci. USA, 121, 10.1073/pnas.2323009121 · DOI
  33. Lacroix, 2018, Microtubule Dynamics Scale with Cell Size to Set Spindle Length and Assembly Timing, Dev. Cell, 45, 496, 10.1016/j.devcel.2018.04.022 · DOI
  34. Rieckhoff, 2020, Spindle scaling is governed by cell boundary regulation of microtubule nucleation, Curr. Biol., 30, 4973, 10.1016/j.cub.2020.10.093 · DOI
  35. Belmont, 1990, Real-Time Visualization of Cell-Cycle Dependent Changes in Microtubule Dynamics in Cytoplasmic Extracts, Cell, 62, 579, 10.1016/0092-8674(90)90022-7 · DOI
  36. Baumgart, 2019, Soluble tubulin is significantly enriched at mitotic centrosomes, J. Cell Biol., 218, 3977, 10.1083/jcb.201902069 · DOI
  37. Qian, 2007, Phosphorylation energy hypothesis: Open chemical systems and their biological functions, Annu. Rev. Phys. Chem., 58, 113, 10.1146/annurev.physchem.58.032806.104550 · DOI
  38. Lan, 2012, The energy-speed-accuracy trade-off in sensory adaptation, Nat. Phys., 8, 422, 10.1038/nphys2276 · DOI
  39. Hill, 1982, Bioenergetics and kinetics of microtubule and actin filament assembly–disassembly, Int. Rev. Cytol., 78, 1, 10.1016/S0074-7696(08)60105-9 · DOI
  40. Foster, 2023, Dissipation and energy propagation across scales in an active cytoskeletal material, Proc. Natl. Acad. Sci. USA, 120, 10.1073/pnas.2207662120 · DOI
  41. Lynch, 2015, The bioenergetic costs of a gene, Proc. Natl. Acad. Sci. USA, 112, 15690, 10.1073/pnas.1514974112 · DOI · Paper page
  42. Kiewisz, 2022, Three-dimensional structure of kinetochore-fibers in human mitotic spindles, eLife, 11, 10.7554/eLife.75459 · DOI
  43. Little, 1961, A proof for the queuing formula l=λw, Oper. Res., 9, 383, 10.1287/opre.9.3.383 · DOI · Paper page
  44. Jayapal, 2010, Multitagging proteomic strategy to estimate protein turnover rates in dynamic systems, J. Proteome Res., 9, 2087, 10.1021/pr9007738 · DOI
  45. Eden, 2011, Proteome half-life dynamics in living human cells, Science, 331, 764, 10.1126/science.1199784 · DOI
  46. Shacter, 1984, Energy consumption in a cyclic phosphorylation/dephosphorylation cascade, J. Biol. Chem., 259, 12260, 10.1016/S0021-9258(20)71348-7 · DOI
  47. Ishikawa, 2011, Building the cell’s antenna, Nat. Rev. Mol. Cell Biol., 12, 222, 10.1038/nrm3085 · DOI
  48. Chien, 2017, Dynamics of the IFT machinery at the ciliary tip, eLife, 6, 10.7554/eLife.28606 · DOI
  49. Kirchhausen, 2001, Three ways to make a vesicle (vol 1, pg 187, 2000), Nat. Rev. Mol. Cell Biol., 2, 216
  50. Wang, 2006, Single molecule measurements of repressor protein 1D diffusion on DNA, Phys. Rev. Lett., 97
  51. Blainey, 2006, A base-excision DNA-repair protein finds intrahelical lesion bases by fast sliding in contact with DNA, Proc. Natl. Acad. Sci. USA, 103, 5752, 10.1073/pnas.0509723103 · DOI
  52. van den Broek, 2006, Real-time observation of DNA looping dynamics of Type IIE restriction enzymes NaeI and NarI, Nucleic Acids Res., 34, 167, 10.1093/nar/gkj432 · DOI
  53. Finkelstein, 2010, Single-molecule imaging reveals mechanisms of protein disruption by a DNA translocase, Nature, 468, 983, 10.1038/nature09561 · DOI
  54. Hammar, 2012, The lac repressor displays facilitated diffusion in living cells, Science, 336, 1595, 10.1126/science.1221648 · DOI
  55. Normanno, 2015, Probing the target search of DNA-binding proteins in mammalian cells using TetR as model searcher, Nat. Commun., 6, 7357, 10.1038/ncomms8357 · DOI
  56. Weber, 2010, Bacterial chromosomal loci move subdiffusively through a viscoelastic cytoplasm, Phys. Rev. Lett., 104, 10.1103/PhysRevLett.104.238102 · DOI
  57. Gabriele, 2022, Dynamics of CTCF- and cohesin-mediated chromatin looping revealed by live-cell imaging, Science, 376, 496, 10.1126/science.abn6583 · DOI · Paper page
  58. Mohammed, 2017, Self-assembling dna nanotubes to connect molecular landmarks, Nat. Nanotechnol., 12, 312, 10.1038/nnano.2016.277 · DOI
  59. Schaffter, 2020, Reconfiguring dna nanotube architectures via selective regulation of terminating structures, ACS Nano, 14, 13451, 10.1021/acsnano.0c05340 · DOI

Metadata

Authors
Kondev, J., Kirschner, M., Garcia, H. G., Salmon, G. L., & Phillips, R.
Affiliations
  • Harvard University (US)
  • California Institute of Technology (US)
Corresponding author
  • Salmon, Gabriel L.
  • Phillips, Rob
Venue
Biophysical Journal
Publisher
Elsevier BV
Published
2026-06
Volume
125
Issue
12
Pages
2812-2837
ISSN
0006-3495 (ISSN-L)
OpenAlex
W4414120941
Cited by
4
References
3
Citations by year
2026: 3
FWCI
1.89
Type
journal article
Language
en
Open access
Locations
  • Biophysical Journal (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion)
  • arXiv (Cornell University) (submittedVersion, cc-by-nc-sa)
  • Europe PMC (PubMed Central) (submittedVersion, cc-by-nc)
  • PubMed Central (submittedVersion, cc-by-nc-sa)
  • PubMed Central (submittedVersion, cc-by-nc)
  • arXiv (Cornell University)
Funders
  • National Institutes of Health
  • Foundation for the National Institutes of Health
  • Simons Foundation
  • The Chan Zuckerberg Initiative (CZIF2024-010479)
  • National Science Foundation (DMR-1610737, MRSEC DMR-2011846, DGE-1745301)
  • Tel Aviv University
Topics
  • Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy of Biology and Scientific Explanation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Microtubule and mitosis dynamics
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Advanced Thermodynamics and Statistical Mechanics
Keywords
biological processes, chromosome segregation, cell division, futile cycle, random trajectories, physics of living systems

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review