TY - GEN
T1 - Randomly Sampling HP-Protein Conformations: Mission Impossible?
AU - Horn, Ruben
AU - van den Berg, Daan
AU - Jansen, Reitze
AU - Verduin, Kristian
AU - van Eck, Okke
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - Creating random individuals for the HP-protein folding is very hard, if not impossible. This has a big impact on the applicability of genetic algorithms, seemingly making it an intractable method for folding. We will demonstrate this by sampling up to 176,000,000 proteins of lengths on lattice dimensions for two experiments. In the first, we randomly sample conformations until a valid one is found. For the second, we inferred distributions from sampled conformations, which capture the probability of sampling zero-collision conformations. Both results show how the probability of randomly sampling a valid individual decreases exponentially with instance size. This immediately prohibits resampling and the usage of repair mechanisms. One way of creating a valid random individual is through backtracking in exponential time, which is everything but suitable. It is hardly surprising that previous studies only use small instances and fail to report how (often) random samples are created. We will also show how these problems are nonexistent for the Traveling Salesman Problem (TSP), which is also -hard.
AB - Creating random individuals for the HP-protein folding is very hard, if not impossible. This has a big impact on the applicability of genetic algorithms, seemingly making it an intractable method for folding. We will demonstrate this by sampling up to 176,000,000 proteins of lengths on lattice dimensions for two experiments. In the first, we randomly sample conformations until a valid one is found. For the second, we inferred distributions from sampled conformations, which capture the probability of sampling zero-collision conformations. Both results show how the probability of randomly sampling a valid individual decreases exponentially with instance size. This immediately prohibits resampling and the usage of repair mechanisms. One way of creating a valid random individual is through backtracking in exponential time, which is everything but suitable. It is hardly surprising that previous studies only use small instances and fail to report how (often) random samples are created. We will also show how these problems are nonexistent for the Traveling Salesman Problem (TSP), which is also -hard.
KW - Constraint hierarchy
KW - Constraints
KW - Evolutionary computing
KW - Genetic algorithms
KW - Protein folding
UR - https://www.scopus.com/pages/publications/105002051390
UR - https://www.scopus.com/pages/publications/105002051390#tab=citedBy
U2 - 10.1007/978-3-031-85252-7_18
DO - 10.1007/978-3-031-85252-7_18
M3 - Conference contribution
AN - SCOPUS:105002051390
SN - 9783031852510
T3 - Studies in Computational Intelligence
SP - 323
EP - 338
BT - Computational Intelligence
A2 - Bäck, Thomas
A2 - van Stein, Niki
A2 - Wagner, Christian
A2 - Garibaldi, Jonathan M.
A2 - Marcelloni, Francesco
A2 - Lam, H.K.
A2 - Cottrell, Marie
A2 - Doctor, Faiyaz
A2 - Filipe, Joaquim
A2 - Warwick, Kevin
A2 - Kacprzyk, Janusz
PB - Springer Nature
T2 - 14th and 15th International Joint Conference on Computational Intelligence, IJCCI 2022 and IJCCI 2023
Y2 - 13 November 2023 through 15 November 2023
ER -