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Wyniki wyszukiwania dla: STRUCTURE PREDICTION
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Impact of AlphaFold on structure prediction of protein complexes: The CASP15‐CAPRI experiment
PublikacjaWe present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody–antigen complexes, and 7 large assemblies. On average 70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups...
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Conformation-family Monte Carlo: A new method for crystal structure prediction
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An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12
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Crystal Structure Prediction by Global Optimization as a Tool for Evaluating Potentials: Role of the Dipole Moment Correction Term in Successful Predictions
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Use of Restraints from Consensus Fragments of Multiple Server Models To Enhance Protein-Structure Prediction Capability of the UNRES Force Field
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Protein structure prediction with the UNRES force-field using Replica-Exchange Monte Carlo-with-Minimization; Comparison with MCM, CSA, and CFMC
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Physics-based protein-structure prediction using a hierarchical protocol based on the UNRES force field: Assessment in two blind tests
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Parametrization of Backbone−Electrostatic and Multibody Contributions to the UNRES Force Field for Protein-Structure Prediction from Ab Initio Energy Surfaces of Model Systems
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A Hierarchical Multiscale Approach to Protein Structure Prediction: Production of Low‐Resolution Packing Arrangements of Helices and Refinement of the Best Models with a United‐Residue Force Field
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Prediction of Protein Structure by Template-Based Modeling Combined with the UNRES Force Field
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Recent improvements in prediction of protein structure by global optimization of a potential energy function
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Reply to “Comment on ‘Crystal Structure Prediction by Global Optimization as a Tool for Evaluating Potentials: Role of the Dipole Moment Correction Term in Successful Predictions'” by B. P. van Eijck and J. Kroon
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UNRES server for physics-based coarse-grained simulations and prediction of protein structure, dynamics and thermodynamics
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Prediction of protein structure using a knowledge-based off-lattice united-residue force field and global optimization methods
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Reversed-phase and normal-phase thin-layer chromatography and their application to the lipophilicity prediction of synthetic pyrethroids based on quantitative structure–retention relationships
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Prediction of protein structure with the coarse-grained UNRES force field assisted by small X-ray scattering data and knowledge-based information
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Performance of protein-structure predictions with the physics-based UNRES force field in CASP11
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Rhamnolipid CMC Prediction
PublikacjaRelationships between the purity, pH, hydrophobicity (log Kow) of the carbon substrate, and the critical micelle concentration (CMC) of rhamnolipid type biosurfactants (RL) were investigated using a quantitative structure–property relationship (QSPR) approach and are presented here for the first time. Measured and literature CMC values of 97 RLs, representing biosurfactants at different stages of purification, were considered....
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Prediction of protein assemblies, the next frontier: The CASP14‐CAPRI experiment
PublikacjaWe present the results for CAPRI Round 50, the 4th joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 12 targets, including 6 dimers, 3 trimers, and 3 higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly...
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Integrated information and prediction Web Service WaterPUCK General concept
PublikacjaIn this paper, general concept of a new method as ‘Integrated information and prediction Web Service WaterPUCK’ for investigation influence of agricultural holdings and land-use structures on coastal waters of the southern Baltic Sea is presented. WaterPUCK Service is focused on determination of the current and future environmental status of the surface water and groundwater located in the Puck District (Poland) and its impact...
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Quality prediction of foil capacitors by acoustic emission signals
PublikacjaJakość i trwałość kondensatorów foliowych jest zależna od ich warunków pracy (np. nadmiarowego napięcia pracy, temperatury, wilgotności) oraz od potencjalnych defektów wprowadzonych na różnych etapach wytwarzania kondensatorów. Nieustanny nacisk na wzrost jakości wytwarzanych elementów przy jednoczesnej redukcji kosztów wytwarzania oznacza, że nowe, tanie i szybkie metody predykcji jakości tych elementów są mocno poszukiwane. W...
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Robust Parameter Estimation and Output Prediction for Reactive Carrier-Load Nonlinear Dynamic Networks
PublikacjaIn this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM) framework is addressed. The PPM is utilised to acquire a piece wise constant time-varying parameter linear structure for the RCLNDNS suitable for the on-line one step ahead prediction that may be applied to monitoring...
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Chemometrics for Selection, Prediction, and Classification of Sustainable Solutions for Green Chemistry—A Review
PublikacjaIn this review, we present the applications of chemometric techniques for green and sustainable chemistry. The techniques, such as cluster analysis, principal component analysis, artificial neural networks, and multivariate ranking techniques, are applied for dealing with missing data, grouping or classification purposes, selection of green material, or processes. The areas of application are mainly finding sustainable solutions...
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Blind prediction of homo‐ and hetero‐protein complexes: The CASP13‐CAPRI experiment
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Prediction of flow boiling heat transfer data for R134a, R600a and R290 in minichannels
PublikacjaIn the paper presented is the analysis of the results of calculations using a model to predict flow boiling of refrigerants such as R134a, R600a and R290. The latter two fluids were not used in development of model semiempirical correction. For that reason the model was verified with present experimental data. The experimental research was conducted for a full range of quality variation and a relatively wide range of mass velocity....
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Prediction of flow boiling heat transfer coefficient for carbon dioxide in minichannels and conventional channels
PublikacjaIn the paper are presented the results of calculations using authors own model to predict heat transfer coefficient during flow boiling for carbon dioxide. The experimental data from various researches were scrutinised conducted for a full range of quality variation and wide range of mass velocity. The aim of the study was to test the sensitivity of the in-house model. The work shows the importance of taking into account surface...
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Advanced Scalar-valued Intensity Measures for Residual Drift Prediction of SMRFs with Fluid Viscous Dampers
PublikacjaMaximum Residual Inter-story Drift Ratio (RIDRmax) plays an important role to specify the state of a structure after severe earthquake and the possibility of repairing the structure. Therefore, it is necessary to predict the RIDRmax of Steel Moment-Resisting Frames (SMRFs) with high reliability by employing powerful Intensity Measures (IMs). This study investigates the efficiency and sufficiency of scalar-valued IMs for predicting...
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Fast and reliable knowledge-based design closure of antennas by means of iterative prediction-correction scheme
PublikacjaA novel framework for expedited antenna optimization with an iterative prediction-correction scheme is proposed. The methodology is comprehensively validated using three real-world antenna structures: narrow-band, dual-band and wideband, optimized under various design scenarios. The keystone of the proposed approach is to reuse designs pre-optimized for various sets of performance specifications and to encode them into metamodels...
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublikacjaIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Nonlinear FEM 2D failure onset prediction of composite shells based on 6-parameter shell theory
PublikacjaWithin the framework of the nonlinear 6-parameter shell theory with the drilling rotation and asymmetric stress measures, the modifications of Tsai-Wu and Hashin laminate failure initiation criteria are proposed. These improvements enable to perform first ply failure estimations taking into account the non-symmetric stress measures. In order to check the validity of the proposed criteria, finite element analyses are performed with...
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Prediction of cast-in-place concrete strength of the extradosed bridge deck based on temperature monitoring and numerical simulations
PublikacjaThe work is devoted to the implementation of a monitoring system for high performance concrete embedded in the span of an extradosed bridge deck using a modified maturity method augmented by numerical simulations conducted by the authors’ FEM code. The paper presents all research stages of bridge construction and considers the conclusions drawn from the results of laboratory tests, field measurements, and numerical calculations....
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Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants
PublikacjaThe genome feature of SARS-CoV-2 leads the virus to mutate and creates new variants of concern. Tackling viral mutations is also an important challenge for the development of a new vaccine. Accordingly, in the present study, we undertook to identify B- and T-cell epitopes with immunogenic potential for eliciting responses to SARS-CoV-2, using computational approaches and its tailoring to coronavirus variants. A total of 47 novel...
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Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants
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Grey wolf optimizer integrated within boosting algorithm: Application in mechanical properties prediction of ultra high-performance concrete including carbon nanotubes
PublikacjaNowadays, the construction industry has increasingly recognized the superior performance characteristics of ultra high-performance concrete (UHPC). Known for its exceptional durability and high tensile strength, UHPC material is revolutionizing structure standards subjected to extreme environmental conditions and heavy loads. This paper explores the enhancement of UHPC with nano- and micromaterials, employing advanced machine-learning...
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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublikacjaOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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Rating Prediction with Contextual Conditional Preferences
PublikacjaExploiting contextual information is considered a good solution to improve the quality of recommendations, aiming at suggesting more relevant items for a specific context. On the other hand, recommender systems research still strive for solving the cold-start problem, namely where not enough information about users and their ratings is available. In this paper we propose a new rating prediction algorithm to face the cold-start...
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Multicomponent ionic liquid CMC prediction
PublikacjaWe created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (Vm), solvent-accessible surface (Sˆ), solvation enthalpy (DsolvGN), concentration of salt (Cs) or alcohol (Ca) and their molecular volumes (Vms and Vma, respectively) were chosen...
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BANKRUPTCY PREDICTION IN VISEGRAD GROUP COUNTRIES
PublikacjaThe novelty of the study is a comprehensive look at the problem of bankruptcy forecasting in Visegrad Group countries (V4) and making a comparison in relation to the achievements obtained in more developed western countries. The conducted research based on a systematic literature review of 151 publications indexed in Scopus and Web of Science and bibliometric analysis. The results showed that the main lines of research are from...
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Ship Resistance Prediction with Artificial Neural Networks
PublikacjaThe paper is dedicated to a new method of ship’s resistance prediction using Artificial Neural Network (ANN). In the initial stage selected ships parameters are prepared to be used as a training and validation sets. Next step is to verify several network structures and to determine parameters with the highest influence on the result resistance. Finally, other parameters expected to impact the resistance are proposed. The research utilizes...
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Bankruptcy Prediction - History, Present and Future.
PublikacjaW artykule przedstawiono krótką wzmiankę dotyczącą dotychczasowych badań w obszarze zagrożenia przedsiębiorstw upadłością, techniki wykorzystywane do budowy modeli prognozowania upadłości przedsiębiorstw oraz metody stosowane w analizie porównawczej tego typu modeli.
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Toward Prediction of Environmental Arctic Change
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numerical prediction of vortex generated by hydrofoil
PublikacjaW pracy przedstawiono wyniki obliczeń programami Fluent i Comet dla płata śruby napędowej. Pola prędkości oraz wirowość za płatem porównano z wynikami pomiarów (LDA- Laser Doppler Anemometry) w tunelu kawitacyjnym Centrum Techik Okrętowych (CTO). Przedstawiono wpływ adaptacji siatki wg różnych kryteriów (lokalnej wirowości lub prędkości) na zgodność wyników obliczeń z danymi eksperymentalnymi.
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COMPARISON OF BLOOD PRESSURE PREDICTION METHODS
PublikacjaIn the paper dierent approaches of predicting blood pressure values are presented. Basically, two methods and theirs modifications are considered. In total, seven algorithms have been examined. Tests have been conducted using both synthetic and clinical data. From our study it follows that none of the examined methods is superior to other.
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Akaike's final prediction error criterion revisited
PublikacjaWhen local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/ tracking purposes. Failure to make the right decisions results...
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Dynamic Bankruptcy Prediction Models for European Enterprises
PublikacjaThis manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and...
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Wyznaczanie współczynnika przejmowania ciepła podczas wrzenia w przepływie dwutlenku węgla (Prediction of flow boling heat transfer coefficient for carbon dioxide in minichannels)
PublikacjaW pracy przedstawiono wyniki obliczeń uzyskane za pomocą własnego modelu półemirycznego dla wybranych danych eksperymentalnych dla wrzenia w przepływie dwutlenku węgla. Metoda obliczeniowa została zweryfikowana z danymi eksperymentalnymi Docoulombiera i innych (2011) oraz Mastrullo i innych (2009). Badania eksperymentalne dotyczą pełnego zakresu zmienności stopnia suchości oraz zakresu prędkości masowej G=200-1200 kg/m2s. rozwijany...
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Modeling the Structure, Dynamics, and Transformations of Proteins with the UNRES Force Field
PublikacjaThe physics-based united-residue (UNRES) model of proteins ( www.unres.pl ) has been designed to carry out large-scale simulations of protein folding. The force field has been derived and parameterized based on the principles of statistical-mechanics, which makes it independent of structural databases and applicable to treat nonstandard situations such as, proteins that contain D-amino-acid residues. Powered by Langevin dynamics...
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Intelligent Decision Forest Models for Customer Churn Prediction
PublikacjaCustomer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....