1. A survey of features used for representing black-box single-objective continuous optimizationGjorgjina Cenikj, Ana Nikolikj, Gašper Petelin, Niki Van Stein, Carola Doerr, Tome Eftimov, 2025, original scientific article Abstract: This survey examines key advancements in designing features to represent optimization problem instances, algorithm instances, and their interactions within the context of single-objective continuous black-box optimization. These features support machine learning tasks such as algorithm selection, algorithm configuration, and problem classification, and they are also used to evaluate the complementarity of benchmark problem sets. We provide a comprehensive overview of problem landscape features, algorithm features, high-level problem-algorithm interaction features, and trajectory features, including the latest works from the past five years. We also point out limitations of the current state-of-the-art and suggest directions for future research.
Keywords: problem landscape features, algorithm features, problem -algorithm trajectory features, problem classification, algorithm selection, algorithm configuration, complementarity analysis
Published in DiRROS: 26.01.2026; Views: 144; Downloads: 79
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2. Low but significant evolutionary potential for growth, phenology and reproduction traits in European beechMarjana Westergren, Juliette Archambeau, Marko Bajc, Rok Damjanić, Adélaïde Theraroz, Hojka Kraigher, Sylvie Oddou-Muratorio, Santiago C. González-Martínez, 2023, complete scientific database of research data Abstract: Local survival of forest tree populations under climate change depends on existing genetic variation and their adaptability to changing environments. Responses to selection were studied in European beech (Fagus sylvatica) under field conditions. A total of 1,087 adult trees, seeds, one-year-old seedlings, and established multiyear saplings were genotyped with 16 nuSSRs. Adult trees were assessed for phenotypic traits related to growth, phenology and reproduction. Parentage and paternity analyses were used to estimate effective female and male fecundity as a proxy of fitness and showed that few parents contributed to successful regeneration. Selection gradients were estimated from the relationship between traits and fecundity, while heritability and evolvability were estimated using mixed models and the breeder’s equation. Larger trees bearing more fruit and early male flowering had higher total fecundity, while trees with longer growth season had lower total fecundity (directional selection). Stabilising selection on spring phenology was found for female fecundity, highlighting the role of late frosts as a selection driver. Selection gradients for other traits varied between measurement years and the offspring cohort used to estimate parental fecundity. Compared to other studies in natural populations, we found low to moderate heritability and evolvability for most traits. Response to selection was higher for growth than for budburst, leaf senescence or reproduction traits, reflecting more consistent selection gradients across years and sex functions, and higher phenotypic variability in the population. Our study provides empirical evidence suggesting that populations of long-lived organisms such as forest trees can adapt locally, even at short-time scales.
Keywords: climate change, Fagus sylvatica, heritability, in situ adaptation, response to selection, selection gradients
Published in DiRROS: 10.09.2025; Views: 406; Downloads: 234
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3. BugBook: Genetics of insects as food and feedChristoph Sandrock, Tomas N. Generalovic, Katy Paul, Gertje Petersen, Eliaou Sellem, Michael Barlett Smith, Miika Tapio, Wael Yakti, Leo W. Beukeboom, David Deruytter, Jana Obšteter, 2025, original scientific article Keywords: human diet, edible insects, demographic inference, insect breeding, population management, farming insects, review, selection cheme, human nutrition
Published in DiRROS: 18.08.2025; Views: 517; Downloads: 375
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5. Genomic insight into the origin, domestication, dispersal, diversification and human selection of Tartary buckwheatYuqi He, Kaixuan Zhang, Yaliang Shi, Mateja Germ, Zlata Luthar, Ivan Kreft, Dagmar Janovská, Vladimir Meglič, Meiliang Zhou, 2024, original scientific article Abstract: Background: Tartary buckwheat, Fagopyrum tataricum, is a pseudocereal crop with worldwide distribution and high nutritional value. However, the origin and domestication history of this crop remain to be elucidated. Results: Here, by analyzing the population genomics of 567 accessions collected worldwide and reviewing historical documents, we find that Tartary buckwheat originated in the Himalayan region and then spread southwest possibly along with the migration of the Yi people, a minority in Southwestern China that has a long history of planting Tartary buckwheat. Along with the expansion of the Mongol Empire, Tartary buckwheat dispersed to Europe and ultimately to the rest of the world. The different natural growth environments resulted in adaptation, especially significant differences in salt tolerance between northern and southern Chinese Tartary buckwheat populations. By scanning for selective sweeps and using a genome-wide association study, we identify genes responsible for Tartary buckwheat domestication and differentiation, which we then experimentally validate. Comparative genomics and QTL analysis further shed light on the genetic foundation of the easily dehulled trait in a particular variety that was artificially selected by the Wa people, a minority group in Southwestern China known for cultivating Tartary buckwheat specifically for steaming as a staple food to prevent lysine deficiency. Conclusions: This study provides both comprehensive insights into the origin and domestication of, and a foundation for molecular breeding for, Tartary buckwheat.
Keywords: domestication, migration, artificial selection, buckwheat, genomics
Published in DiRROS: 31.12.2024; Views: 919; Downloads: 431
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6. Identification of population-informative markers from high-density genotyping data through combined feature selection and machine learning algorithms : Application to European autochthonous and cosmopolitan pig breedsGiuseppina Schiavo, Francesca Bertolini, Samuele Bovo, Giuliano Galimberti, Maria Muñoz, Riccardo Bozzi, Marjeta Čandek-Potokar, Cristina Ovilo, Luca Fontanesi, 2024, original scientific article Keywords: genome, population genomics, random forest, signatures of selection, SNP
Published in DiRROS: 31.12.2024; Views: 785; Downloads: 275
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7. Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis costFilip Buric, Sandra Viknander, Xiaozhi Fu, Oliver Lemke, Oriol Gracia Carmona, Jan Zrimec, Lukasz Szyrwiel, Michael Mülleder, Markus Ralser, Aleksej Zelezniak, 2025, original scientific article Abstract: Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, an amino acid sequence is tailored to meet the required abundance of a proteome, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here we show that the amino acid sequence alone encodes over half of protein abundance variation across all domains of life, ranging from bacteria to mouse and human. With an attempt to go beyond predictions, we trained a manageable-size Transformer model to interpret latent factors predictive of protein abundances. Intuitively, the model's attention focused on the protein's structural features linked to stability and metabolic costs related to protein synthesis. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations which increase predicted abundance have significantly altered protein polarity and hydrophobicity, underscoring a connection between protein structural features and abundance. Through molecular dynamics simulations we revealed that abundance-enhancing mutations possibly contribute to protein thermostability by increasing rigidity, which occurs at a lower synthesis cost.
Keywords: molecular biology, biotechnology, bioinformatics, deep learning, gene expression, synthetic biology, protein abundance, amino acid sequence, evolutionary selection, transformer model, MGEM (Mutation guided by an embedded manifold)
Published in DiRROS: 17.12.2024; Views: 1107; Downloads: 615
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10. Learning macroscopic equations of motion from dissipative particle dynamics simulations of fluidsMatevž Jug, Tilen Potisk, Daniel Svenšek, Matej Praprotnik, 2024, original scientific article Keywords: sparsity, model selection, particle simulations, macroscopic dynamics, regression
Published in DiRROS: 26.09.2024; Views: 791; Downloads: 1064
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