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  1. Book ; Online: Ambitions for theory in the physics of life

    Bialek, William

    2024  

    Abstract: Theoretical physicists have been fascinated by the phenomena of life for more than a century. As we engage with more realistic descriptions of living systems, however, things get complicated. After reviewing different reactions to this complexity, I ... ...

    Abstract Theoretical physicists have been fascinated by the phenomena of life for more than a century. As we engage with more realistic descriptions of living systems, however, things get complicated. After reviewing different reactions to this complexity, I explore the optimization of information flow as a potentially general theoretical principle. The primary example is a genetic network guiding development of the fly embryo, but each idea also is illustrated by examples from neural systems. In each case, optimization makes detailed, largely parameter-free predictions that connect quantitatively with experiment

    Comment: Lectures at the 2023 Les Houches Summer School, Theoretical Biophysics
    Keywords Physics - Biological Physics ; Quantitative Biology - Molecular Networks ; Quantitative Biology - Neurons and Cognition
    Publishing date 2024-01-27
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: On the dimensionality of behavior.

    Bialek, William

    Proceedings of the National Academy of Sciences of the United States of America

    2022  Volume 119, Issue 18, Page(s) e2021860119

    Abstract: There is a growing effort in the “physics of behavior” that aims at complete quantitative characterization of animal movements under more complex, naturalistic conditions. One reaction to the resulting explosion of high-dimensional data is the search for ...

    Abstract There is a growing effort in the “physics of behavior” that aims at complete quantitative characterization of animal movements under more complex, naturalistic conditions. One reaction to the resulting explosion of high-dimensional data is the search for low-dimensional structure. Here I try to define more clearly what we mean by the dimensionality of behavior, where observable behavior may consist of either continuous trajectories or sequences of discrete states. This discussion also serves to isolate situations in which the dimensionality of behavior is effectively infinite.
    MeSH term(s) Animals ; Behavior, Animal/physiology ; Environment ; Ethology
    Language English
    Publishing date 2022-04-29
    Publishing country United States
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
    ZDB-ID 209104-5
    ISSN 1091-6490 ; 0027-8424
    ISSN (online) 1091-6490
    ISSN 0027-8424
    DOI 10.1073/pnas.2021860119
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    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  3. Article ; Online: Long Timescales, Individual Differences, and Scale Invariance in Animal Behavior.

    Bialek, William / Shaevitz, Joshua W

    Physical review letters

    2024  Volume 132, Issue 4, Page(s) 48401

    Abstract: The explosion of data on animal behavior in more natural contexts highlights the fact that these behaviors exhibit correlations across many timescales. However, there are major challenges in analyzing these data: records of behavior in single animals ... ...

    Abstract The explosion of data on animal behavior in more natural contexts highlights the fact that these behaviors exhibit correlations across many timescales. However, there are major challenges in analyzing these data: records of behavior in single animals have fewer independent samples than one might expect. In pooling data from multiple animals, individual differences can mimic long-ranged temporal correlations; conversely, long-ranged correlations can lead to an overestimate of individual differences. We suggest an analysis scheme that addresses these problems directly, apply this approach to data on the spontaneous behavior of walking flies, and find evidence for scale-invariant correlations over nearly three decades in time, from seconds to one hour. Three different measures of correlation are consistent with a single underlying scaling field of dimension Δ=0.180±0.005.
    MeSH term(s) Animals ; Individuality ; Behavior, Animal
    Language English
    Publishing date 2024-02-09
    Publishing country United States
    Document type Journal Article
    ZDB-ID 208853-8
    ISSN 1079-7114 ; 0031-9007
    ISSN (online) 1079-7114
    ISSN 0031-9007
    DOI 10.1103/PhysRevLett.132.048401
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  4. Article ; Online: Long time scales, individual differences, and scale invariance in animal behavior.

    Bialek, William / Shaevitz, Joshua W

    ArXiv

    2023  

    Abstract: The explosion of data on animal behavior in more natural contexts highlights the fact that these behaviors exhibit correlations across many time scales. But there are major challenges in analyzing these data: records of behavior in single animals have ... ...

    Abstract The explosion of data on animal behavior in more natural contexts highlights the fact that these behaviors exhibit correlations across many time scales. But there are major challenges in analyzing these data: records of behavior in single animals have fewer independent samples than one might expect; in pooling data from multiple animals, individual differences can mimic long-ranged temporal correlations; conversely long-ranged correlations can lead to an over-estimate of individual differences. We suggest an analysis scheme that addresses these problems directly, apply this approach to data on the spontaneous behavior of walking flies, and find evidence for scale invariant correlations over nearly three decades in time, from seconds to one hour. Three different measures of correlation are consistent with a single underlying scaling field of dimension $\Delta = 0.180\pm 0.005$.
    Language English
    Publishing date 2023-04-19
    Publishing country United States
    Document type Preprint
    ISSN 2331-8422
    ISSN (online) 2331-8422
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  5. Article ; Online: Perspectives on theory at the interface of physics and biology.

    Bialek, William

    Reports on progress in physics. Physical Society (Great Britain)

    2017  Volume 81, Issue 1, Page(s) 12601

    Abstract: Theoretical physics is the search for simple and universal mathematical descriptions of the natural world. In contrast, much of modern biology is an exploration of the complexity and diversity of life. For many, this contrast is prima facie evidence that ...

    Abstract Theoretical physics is the search for simple and universal mathematical descriptions of the natural world. In contrast, much of modern biology is an exploration of the complexity and diversity of life. For many, this contrast is prima facie evidence that theory, in the sense that physicists use the word, is impossible in a biological context. For others, this contrast serves to highlight a grand challenge. I am an optimist, and believe (along with many colleagues) that the time is ripe for the emergence of a more unified theoretical physics of biological systems, building on successes in thinking about particular phenomena. In this essay I try to explain the reasons for my optimism, through a combination of historical and modern examples.
    MeSH term(s) Biology/methods ; Humans ; Interdisciplinary Research/methods ; Physics/methods
    Language English
    Publishing date 2017-12-07
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Review
    ZDB-ID 205657-4
    ISSN 1361-6633 ; 0034-4885
    ISSN (online) 1361-6633
    ISSN 0034-4885
    DOI 10.1088/1361-6633/aa995b
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    In stock of ZB MED Bonn / Germany

    Z 52/38: Show issues

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  6. Book ; Online: Long time scales, individual differences, and scale invariance in animal behavior

    Bialek, William / Shaevitz, Joshua W.

    2023  

    Abstract: The explosion of data on animal behavior in more natural contexts highlights the fact that these behaviors exhibit correlations across many time scales. But there are major challenges in analyzing these data: records of behavior in single animals have ... ...

    Abstract The explosion of data on animal behavior in more natural contexts highlights the fact that these behaviors exhibit correlations across many time scales. But there are major challenges in analyzing these data: records of behavior in single animals have fewer independent samples than one might expect; in pooling data from multiple animals, individual differences can mimic long-ranged temporal correlations; conversely long-ranged correlations can lead to an over-estimate of individual differences. We suggest an analysis scheme that addresses these problems directly, apply this approach to data on the spontaneous behavior of walking flies, and find evidence for scale invariant correlations over nearly three decades in time, from seconds to one hour. Three different measures of correlation are consistent with a single underlying scaling field of dimension $\Delta = 0.180\pm 0.005$.
    Keywords Quantitative Biology - Neurons and Cognition ; Condensed Matter - Disordered Systems and Neural Networks ; Quantitative Biology - Quantitative Methods
    Subject code 612
    Publishing date 2023-04-19
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Emergence of local irreversibility in complex interacting systems.

    Lynn, Christopher W / Holmes, Caroline M / Bialek, William / Schwab, David J

    Physical review. E

    2023  Volume 106, Issue 3-1, Page(s) 34102

    Abstract: Living systems are fundamentally irreversible, breaking detailed balance and establishing an arrow of time. But how does the evident arrow of time for a whole system arise from the interactions among its multiple elements? We show that the local evidence ...

    Abstract Living systems are fundamentally irreversible, breaking detailed balance and establishing an arrow of time. But how does the evident arrow of time for a whole system arise from the interactions among its multiple elements? We show that the local evidence for the arrow of time, which is the entropy production for thermodynamic systems, can be decomposed. First, it can be split into two components: an independent term reflecting the dynamics of individual elements and an interaction term driven by the dependencies among elements. Adapting tools from nonequilibrium physics, we further decompose the interaction term into contributions from pairs of elements, triplets, and higher-order terms. We illustrate our methods on models of cellular sensing and logical computations, as well as on patterns of neural activity in the retina as it responds to visual inputs. We find that neural activity can define the arrow of time even when the visual inputs do not, and that the dominant contribution to this breaking of detailed balance comes from interactions among pairs of neurons.
    Language English
    Publishing date 2023-02-17
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2844562-4
    ISSN 2470-0053 ; 2470-0045
    ISSN (online) 2470-0053
    ISSN 2470-0045
    DOI 10.1103/PhysRevE.106.034102
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  8. Book ; Online: How accurately must cells measure the concentrations of signaling molecules?

    Bauer, Marianne / Bialek, William

    2022  

    Abstract: Information of relevance to the organism often is represented by the concentrations of particular molecules inside a cell. As outside observers we can now measure these concentrations precisely, but the cell's own mechanisms must be noisier. We show that, ...

    Abstract Information of relevance to the organism often is represented by the concentrations of particular molecules inside a cell. As outside observers we can now measure these concentrations precisely, but the cell's own mechanisms must be noisier. We show that, in certain limits, there is a universal tradeoff between the information capacity of these concentration measurements and the amount of relevant information that is captured, a version of the information bottleneck problem. This universal tradeoff is confirmed, quantitatively, in an analysis of the positional information encoded by the gap genes in the developing fly embryo.
    Keywords Physics - Biological Physics ; Quantitative Biology - Molecular Networks
    Publishing date 2022-12-23
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Exactly solvable statistical physics models for large neuronal populations.

    Lynn, Christopher W / Yu, Qiwei / Pang, Rich / Bialek, William / Palmer, Stephanie E

    ArXiv

    2023  

    Abstract: Maximum entropy methods provide a principled path connecting measurements of neural activity directly to statistical physics models, and this approach has been successful for populations ... ...

    Abstract Maximum entropy methods provide a principled path connecting measurements of neural activity directly to statistical physics models, and this approach has been successful for populations of
    Language English
    Publishing date 2023-10-16
    Publishing country United States
    Document type Preprint
    ISSN 2331-8422
    ISSN (online) 2331-8422
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  10. Article ; Online: Decomposing the Local Arrow of Time in Interacting Systems.

    Lynn, Christopher W / Holmes, Caroline M / Bialek, William / Schwab, David J

    Physical review letters

    2022  Volume 129, Issue 11, Page(s) 118101

    Abstract: We show that the evidence for a local arrow of time, which is equivalent to the entropy production in thermodynamic systems, can be decomposed. In a system with many degrees of freedom, there is a term that arises from the irreversible dynamics of the ... ...

    Abstract We show that the evidence for a local arrow of time, which is equivalent to the entropy production in thermodynamic systems, can be decomposed. In a system with many degrees of freedom, there is a term that arises from the irreversible dynamics of the individual variables, and then a series of non-negative terms contributed by correlations among pairs, triplets, and higher-order combinations of variables. We illustrate this decomposition on simple models of noisy logical computations, and then apply it to the analysis of patterns of neural activity in the retina as it responds to complex dynamic visual scenes. We find that neural activity breaks detailed balance even when the visual inputs do not, and that this irreversibility arises primarily from interactions between pairs of neurons.
    MeSH term(s) Entropy ; Neurons/physiology
    Language English
    Publishing date 2022-09-22
    Publishing country United States
    Document type Journal Article
    ZDB-ID 208853-8
    ISSN 1079-7114 ; 0031-9007
    ISSN (online) 1079-7114
    ISSN 0031-9007
    DOI 10.1103/PhysRevLett.129.118101
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