scholarly journals Repertoire-Based Diagnostics Using Statistical Biophysics

2019 ◽  
Author(s):  
Rohit Arora ◽  
Joseph Kaplinsky ◽  
Anthony Li ◽  
Ramy Arnaout
Keyword(s):  
Amino Acid ◽  
Cell Receptor ◽  
Vaccination Status ◽  
Principle Of Maximum Entropy ◽  
Compact Representations ◽  
Maxent Modeling ◽  
Pure Amino Acid ◽  
And Training ◽  
Principle Of Maximum ◽  
Amino Acid Alphabet

AbstractA fundamental challenge in immunology is diagnostic classification based on repertoire sequence. We used the principle of maximum entropy (MaxEnt) to build compact representations of antibody (IgH) and T-cell receptor (TCRβ) CDR3 repertoires based on the statistical biophysical patterns latent in the frequency and ordering of repertoires’ constituent amino acids. This approach results in substantial advantages in quality, dimensionality, and training speed compared to MaxEnt models based solely on the standard 20-letter amino-acid alphabet. Descriptor-based models learn patterns that pure amino-acid-based models cannot. We demonstrate the utility of descriptor models by successfully classifying influenza vaccination status (AUC=0.97, p=4×10-3), requiring only 31 samples from 14 individuals. Descriptor-based MaxEnt modeling is a powerful new method for dissecting, encoding, and classifying complex repertoires.

Information mechanics

2017 ◽  
Author(s):  
Sandip Tiwari
Keyword(s):  
Information Flow ◽  
Irreversible Processes ◽  
State Machines ◽  
Science And Engineering ◽  
Von Neumann ◽  
Principle Of Maximum Entropy ◽  
Information Manipulation ◽  
Classical Quantum ◽  
Physical Laws ◽  
Principle Of Maximum

Information is physical, so its manipulation through devices is subject to its own mechanics: the science and engineering of behavioral description, which is intermingled with classical, quantum and statistical mechanics principles. This chapter is a unification of these principles and physical laws with their implications for nanoscale. Ideas of state machines, Church-Turing thesis and its embodiment in various state machines, probabilities, Bayesian principles and entropy in its various forms (Shannon, Boltzmann, von Neumann, algorithmic) with an eye on the principle of maximum entropy as an information manipulation tool. Notions of conservation and non-conservation are applied to example circuit forms folding in adiabatic, isothermal, reversible and irreversible processes. This brings out implications of fluctuation and transitions, the interplay of errors and stability and the energy cost of determinism. It concludes discussing networks as tools to understand information flow and decision making and with an introduction to entanglement in quantum computing.

scholarly journals To Be or to Have Been Lucky, That Is the Question

Philosophies ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 57
Author(s):  
Antony Lesage ◽  
Jean-Marc Victor
Keyword(s):  
High Risk ◽  
Maximum Entropy ◽  
Chronic Diseases ◽  
Statistical Test ◽  
Low Risk ◽  
Principle Of Maximum Entropy ◽  
Ex Ante ◽  
Social Opportunities ◽  
Global Population ◽  
Principle Of Maximum

Is it possible to measure the dispersion of ex ante chances (i.e., chances “before the event”) among people, be it gambling, health, or social opportunities? We explore this question and provide some tools, including a statistical test, to evidence the actual dispersion of ex ante chances in various areas, with a focus on chronic diseases. Using the principle of maximum entropy, we derive the distribution of the risk of becoming ill in the global population as well as in the population of affected people. We find that affected people are either at very low risk, like the overwhelming majority of the population, but still were unlucky to become ill, or are at extremely high risk and were bound to become ill.

scholarly journals A Weakly Informative Prior for Resonance Frequencies

2021 ◽  
Vol 3 (1) ◽  
pp. 2
Author(s):  
Marnix Van Soom ◽  
Bart de Boer
Keyword(s):  
Arbitrary Order ◽  
Evidence Based ◽  
Inductive Bias ◽  
New Class ◽  
Selection Problems ◽  
Principle Of Maximum Entropy ◽  
Informative Prior ◽  
Resonance Frequencies ◽  
Principle Of Maximum ◽  
Robust Evidence

We derive a weakly informative prior for a set of ordered resonance frequencies from Jaynes’ principle of maximum entropy. The prior facilitates model selection problems in which both the number and the values of the resonance frequencies are unknown. It encodes a weakly inductive bias, provides a reasonable density everywhere, is easily parametrizable, and is easy to sample. We hope that this prior can enable the use of robust evidence-based methods for a new class of problems, even in the presence of multiplets of arbitrary order.

scholarly journals Nutrition Studies on Pure Amino Acid

1959 ◽  
Vol 12 (4) ◽  
pp. 269-275
Author(s):  
Saburoh Watanabe
Keyword(s):  
Amino Acid ◽  
Pure Amino Acid
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