24 papers · ranked by Valyu relevance
Alexander G. Lucaci, Jordan D. Zehr, Stephen D. Shank, Dave Bouvier + 6 more
'Alexander Ostrovsky' 'Han Mei' 'Anton Nekrutenko' 'Darren P. Martin' 'Sergei L. Kosakovsky Pond' 'Vladimir Makarenkov'] An important unmet need revealed by the COVID-19 pandemic is the near-real-time identification of potentially fitness-altering mutations within rapidly growing SARS-CoV-2 lineages. Although powerful…
Laura Leventhal, Karen J. Bai, Madeline A. E. Peters, Emily J. Austen + 2 more
Net selection on a trait reflects the association of phenotype to fitness, across an entire life cycle. This longitudinal estimate of selection can be viewed as the summation of selection episodes, each characterized by a cross-sectional estimate. Selection may be consistent in direction and strength across episodes…
Paola Handal-Marquez, Hoai Nguyen, Vitor B. Pinheiro
Directed evolution is a powerful tool that can bypass gaps in our understanding of the sequence-function relationship of proteins and still isolate variants with desired activities, properties, and substrate specificities. The rise of directed evolution platforms for polymerase engineering has accelerated the isolation…
Anne C.M. Jansen, Mario P.L. Calus, Yvonne C.J. Wientjes
The aim of animal breeding is to select the genetically best animals in the current generation to improve the performance of future generations for a specific breeding goal. With the continuous shift in breeding goals towards more balanced breeding, new traits may become of interest. Knowledge of the (indirect)…
V. S. Sai Subhash Mahamkali, Jensina Davis, Kyle Linders, James C. Schnable + 2 more
Crop domestication and subsequent improvement under modern agronomic conditions have altered the nitrogen (N) regimes experienced by crops, yet how selection has reshaped the genetic architecture of phenotypic responses to N availability remains poorly understood. Here, we integrated population genomic analyses of n =…
Authors not listed
The identification of kinetically feasible reaction pathways that connect a reactant to its product, including numerous intermediates and transition states, is crucial for predicting chemical reactions and elucidating reaction mechanisms. However, as molecular systems become increasingly complex or larger, the number…
A. Carvajal-Rodríguez
Sexual selection plays a crucial role in modern evolutionary theory, offering valuable insight into evolutionary patterns and species diversity. Recently, a comprehensive definition of sexual selection has been proposed, defining it as any selection that arises from fitness differences associated with nonrandom success…
Matthew E. Carroll, Luis G. Riera, Bradley A. Miller, Philip M. Dixon + 3 more
Spatial adjustments are used to improve the estimate of plot seed yield across crops and geographies. Moving mean and P-Spline are examples of spatial adjustment methods used in plant breeding trials to deal with field heterogeneity. Within trial spatial variability primarily comes from soil feature gradients, such as…
Shervin Zakeri, Prasenjit Chatterjee, Dimitri Konstantas, Fatih Ecer
A large number of materials and various criteria fashion material selection problems as complex multi-criteria decision-making (MCDM) problems. This paper proposes a new decision-making method called the simple ranking process (SRP) to solve complex material selection problems. The accuracy of the criteria weights has…
Zhila Yaseen Taha, Abdulhady Abas Abdullah, Tarik A. Rashid
Methods and Applications Authors: ['Zhila Yaseen Taha' 'Abdulhady Abas Abdullah' 'Tarik A. Rashid'] Analyzing large datasets to select optimal features is one of the most important research areas in machine learning and data mining. This feature selection procedure involves dimensionality reduction which is crucial in…
Authors not listed
Machine learning (ML) has emerged as a transformative approach to accelerate material discovery. A critical challenge in building predictive ML models is the selection of representative and informative training datasets from large databases. In this study, we present a framework that integrates inducing points and…
Keshavarzian, Alireza, Valaee, Shahrokh
Time series classification stands as a pivotal and intricate challenge across various domains, including finance, healthcare, and industrial systems. In contemporary research, there has been a notable upsurge in exploring feature extraction through random sampling. Unlike deep convolutional networks, these methods…
Authors not listed
This paper addresses the challenges in cell line development (CLD), the lengthy and ambiguous clone screening in upstream biopharmaceutical production. Typically, only a small subset of the later stages of CLD data is used for manually selecting lead clones. Addressing this issue, we introduce a multivariate data…
Chanuka Don Samarasinghage, Dhruv Gulabani
Trajectory analysis is not only about obtaining movement data, but it is also of paramount importance in understanding the pattern in which an object moves through space and time, as well as in predicting its next move. Due to the significant interest in the area, data collection has improved substantially, resulting…
Muhammad Rajabinasab, Anton Danholt Lautrup, Tobias Hyrup, Arthur Zimek
'Arthur Zimek'] Abstract. Expressive evaluation metrics are indispensable for informative experiments in all areas, and while several metrics are established in some areas, in others, such as feature selection, only indirect or otherwise limited evaluation metrics are found. In this paper, we propose a novel evaluation…
José Barrera-García, Felipe Cisternas-Caneo, Broderick Crawford, Mariam Gómez Sánchez + 2 more
Feature selection is becoming a relevant problem within the field of machine learning. The feature selection problem focuses on the selection of the small, necessary, and sufficient subset of features that represent the general set of features, eliminating redundant and irrelevant information. Given the importance of…
Hossein Sabouri, Sayed Javad Sajadi
Hybrid breeding is fast becoming a key instrument in plants' crop productivity. Grain yield performance of hybrids (F1) under different parental genetic features has consequently received considerable attention in the literature. The main objective of this study was to introduce a new method, known as AI_HIB under…
Justus T. Metternich, Sujit K. Patjoshi, Tanuja Kistwal, Sebastian Kruss
Optical sensors/probes are powerful tools to identify and image (biological) molecules. Because of their optoelectronic properties, nanomaterials are often used as building blocks. Such nanosensors are assembled from an optically sensitive nanomaterial, a (biological) recognition unit, and linker chemistry that…
Chengcheng Liu, Xuandong Wang, Weidong Cai, Jiahui Yang + 2 more
'Tomasz Trzepieciński'] Most failures in steel materials are due to fatigue damage, so it is of great significance to analyze the key features of fatigue strength (FS) in order to improve fatigue performance. This study collected data on the fatigue strength of steel materials and established a predictive model for FS…
Kalaipriyan Thirugnanasambandam, Jayalakshmi Murugan, Rajakumar Ramalingam, Mamoon Rashid + 5 more
Background Feature selection is a vital process in data mining and machine learning approaches by determining which characteristics, out of the available features, are most appropriate for categorization or knowledge representation. However, the challenging task is finding a chosen subset of elements from a given set…
Ruru Liu, Rencheng Fang, Tao Zeng, Hongmei Fei + 5 more
'Pengxiang Zuo' 'Liping Xu' 'Wei Liu' 'Heming Jia'] Feature selection (FS) constitutes a critical stage within the realms of machine learning and data mining, with the objective of eliminating irrelevant features while guaranteeing model accuracy. Nevertheless, in datasets featuring a multitude of features, choosing…
Nicolas Ngo, Pierre Michel, Roch Giorgi
\usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varvec{\gamma }$$\end{document} γ -metric Authors: ['Nicolas Ngo' 'Pierre Michel' 'Roch Giorgi'] Background The…
Marco Blanchini, Giovanna Maria Dimitri, Benedetta Tondi, Tarcisio Lancioni + 1 more
Visual Sentiment Analysis (VSA) is a challenging task due to the vast diversity of emotionally salient images and the inherent difficulty of acquiring sufficient data to capture this variability comprehensively. Key obstacles include building large-scale VSA datasets and developing effective methodologies that enable…
Niloufar Mehrabi, Sayed Pedram Haeri Boroujeni, Elnaz Pashaei
The Horse Herd Optimization Algorithm (HOA) is a new meta-heuristic algorithm based on the behaviors of horses at different ages. The HOA was introduced recently to solve complex and high-dimensional problems. This paper proposes a binary version of the Horse Herd Optimization Algorithm (BHOA) in order to solve…