Computational Theories of Evolution
2014-03-17..2014-03-21
Berkeley, United States
who it's for
evolutionary theorists, theoretical computer scientists, population geneticists, computational biologists, machine learning researchers, systems biologists, molecular evolutionary biologists
topics
evolvability theory and models; autocatalytic RAF detection algorithm; multiplicative weights in evolution; promoter-as-Markov-chain regulation; translation read-through and cryptic sequences; two-break genome rearrangement distance; multiplicative drift theorem runtime bounds; 1+1 evolutionary algorithm optimal mutation; adaptive immune system as learning algorithm; PLS-hardness of fitness landscapes; Gillespie simulations of RNA networks; mutual information fitness for patterning
| title | author | length |
|---|---|---|
| Presentation of Evolvability | Leslie Valiant, Vitaly Feldman, Varun Kanade, Elaine Angelino | 02h 03m |
Defines genomes as computable functions and fitness as an empirical performance against an ideal function under an unknown distribution, then shows evolution… | ||
| Molecular Errors, Cryptic Sequences, and Evolvability | Joanna Masel | 54m |
Model shows a speed–accuracy tradeoff driving an either/or outcome: cells evolve either low error rates with broad proofreading or high error rates that purge… | ||
| Autocatalytic Sets and Models of Early Life | Mike Steel | 44m |
Proves that self‑sustaining autocatalytic sets (RAFs) appear when the average number of reactions catalyzed per molecule μ grows about linearly with polymer… | ||
| The Evolution of Evolvability | Lee Altenberg | 52m |
Argues that evolvability increases by individual-level selection on which new genes get fixed, not by group selection, and demonstrates it with math and… | ||
| Presentation of Evolution and Algorithms | Christos Papadimitriou, Umesh Vazirani | 01h 04m |
Shows that standard population genetics under weak selection implements the multiplicative weights update: allele frequencies follow the MW equations, so… | ||
| What Limits the Efficiency of Natural Selection? | Nick Barton | 40m |
Argues that overall limits on selection come from measurable quantities not buzzwords, using population- and quantitative-genetic formulas: human genome… | ||
| Interaction-based Evolution: How Natural Selection and Non-accidental Mutation Work Together | Adi Livnat | 01h 07m |
Argues mutation is a biologically directed, computational process that combines information from multiple loci rather than pure accident, supported by… | ||
| Variation in Regulatory Information Within and Between Species | Mike Snyder | 48m |
Maps chromatin marks in 19 people and finds enhancer marks most variable while promoters are more stable; activity frequently toggles on/off but enhancers… | ||
| Birth and Death of Fragile Chromosomal Regions in Mammalian Evolution | Pavel Pevzner | 59m |
Computational proof shows the random breakage model fails: breakpoint graphs and a two-break distance algorithm give a minimum of 245 two-break events between… | ||
| Evolution of Dynamic Models for Embryonic Patterning and Their Geometric Representation | Eric Siggia | 52m |
Uses an evolutionary algorithm to mutate network topology and parameters of pseudo‑biochemical nodes, evaluating fitness as mutual information fitness between… | ||
| How to Treat Evolutionary Algorithms as Ordinary Randomized Algorithms | Carsten Witt | 52m |
Drift analysis turns one-step expected progress into global runtime bounds, using the multiplicative drift theorem to prove the 1+1 EA finds OneMax and every… | ||
| Measurement Scale and the Dissipation of Information Shape Biological Pattern | Steve Frank | 48m |
Argues that a robustness–decay duality drives evolution: higher-level controllers (RAID-like redundancy) permit cheaper, sloppier parts that then decay and… | ||
| A New Research Program: Evolutionary Neurodynamics | Chrisantha Fernando | 47m |
Hypothesis: the brain contains replicators in the brain that undergo selection during thinking and sleep, enabling open‑ended search. Models show three… | ||
| Generalization of the Central Models of Evolutionary Biology in the (post)Genomic Era | Eugene Koonin | 01h 00m |
Comparative analysis of hundreds of microbial genomes using the ATGC database and the COUNT maximum‑likelihood birth‑death‑innovation model reveals a robust… | ||
| Presentation of Evolvability | Paul Valiant | 44m |
Defines a formal model where genomes encode hypothesis functions, evolution samples finite examples, and selection keeps the best empirical performer; proves… | ||
| The Blessing and the Curse of Multiplicative Updates | Manfred Warmuth | 59m |
Multiplicative updates multiply nonnegative weights and recover Bayes via prior×likelihood, implemented physically with 10^20 strands in in vitro selection… | ||
| Algorithms for Multityped Branching Processes | Mihalis Yannakakis | 57m |
Algorithms compute the extinction probabilities of multitype branching processes by solving the monotone system of probabilistic polynomial fixed‑point… | ||
| The Rate of Progress of Evolution | Nicholas Pippenger | 54m |
Proves a lower bound that fixing n unlinked loci by selection requires on the order of the square root of n generations under explicit assumptions: haploid… | ||
| Evolution in Fluctuating Environments | Edo Kussell | 47m |
Microfluidic mother machine modification grows small E. coli populations (10–60 cells) with second-scale nutrient switching and fluorescent reporters… | ||
| The Adaptive Immune System as a Learning Algorithm | Shishi Luo | 39m |
Frames HIV response as a search problem: simulate B cell–antigen shape space (bit strings with Hamming distance or longest common substring) and run… | ||
| Satisfiability and Evolution | Andrew Wan | 33m |
Claims that, under random mating and full recombination, tracking only marginal allele frequencies via product distributions (using Nagylaki's theorem to… | ||
| The Dynamics of Complex Adaptation | Daniel Weissman | 34m |
Argues that complex adaptations with k mutations succeed when the combination’s selective advantage exceeds local recombination so it avoids breakup, gives the… | ||
| A Population Genetic Model of Disease Susceptibility and Other Quantitative Traits | Guy Sella | 50m |
Uses Fisher's geometric model with Gaussian stabilizing fitness, infinite-sites mutation and diffusion approximations to derive closed-form allele dynamics and… | ||
| Defensive Complexity in Antagonistic Coevolution | Carl Bergstrom | 51m |
Argues that immune control logic can be designed so pathogens face exponential learning time to subvert it, despite much faster viral evolution (≈100,000×… | ||
| Darwinian Machine Learning: Principles of Machine Learning in Evo-devo, Evo-eco and Evolutionary... | Richard Watson | 57m |
Argues that evolving regulatory matrices (recurrent gene networks) implements Hebbian learning so evolved GRNs become Hopfield-like memories that reconstruct… | ||
| A Few Comments (& Questions!) from a Condensed Matter Physicist | Daniel Fisher | 24m |
Estimates put total bacterial cell divisions across Earth near 10^40 cell divisions, coming from ~10^30 individuals over ~10^12 generations, so rare events can… | ||
| Non-Adaptive Evolvability | Jeff Clune | 46m |
Uses Avida digital organisms to show natural selection drives mutation rates down on rugged fitness landscapes, producing order-of-magnitude lower mutation… | ||
| Complexity of Evolutionary Equilibria in Static Fitness Landscapes | Artem Kaznatcheev | 31m |
Shows that finding local peaks on static NK fitness landscapes is provably hard: for k ≥ 2 the problem is PLS-complete, many adaptive paths have exponential… | ||
| Explaining Adaptation in Genetic Algorithms with Uniform Crossover | Keki Burjorjee | 33m |
Proposes the hyper-climbing hypothesis: genetic algorithms with uniform crossover implement a decimation-style global search that detects coarse schema… | ||
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