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The Biocompatibility and Self-Healing Effect of a Biopolymer’s Coating on Zn Alloy for Biomedical Applications
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Optimization of the Geothermal Energy for District Heating in the Polish Tatras Region: A Case Study
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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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A study HIPERLAN-type noncooperative medium access control setting in a wireless LAN
PublicationDla dostępu MAC przeanalizowano strategię określania długości transmisji w fazie eliminacji zakładając indywidualną optymalizację uzyskanego pasma komunikacyjnego. Zaproponowano różne warianty polityki wyłaniania zwycięzcy eliminacji, mające na celu wyrównanie szans stacji kooperacyjnych i niekooperacyjnych.
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Searching for evaluation procedures for Web based courses - cases from EU projects
PublicationCentrum Edukacji Niestacjonarnej Politechniki Gdańskiej realizuje projekty Unii Europejskiej od 1997 roku. Większość projektów była ukierunkowana na dostarczanie kursów internetowych. Jednak nie wszystkie powstałe kursy mogą być wykorzystane jako dobrej jakości, gotowy do wprowadzenia produkt. W artykule, na bazie doświadczeń nabytych podczas realizacji projektów Leonardo da Vinci (1998-2004), przedstawiono ocenę jakości i osiągniętej...
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Heating caused by a non periodic ultrasound. Theory and calculations on pulse and stationary sources.
PublicationPrzedstawiono teorię ewolucji ogrzewania na skutek przejścia fali akustycznej każdego typu. Przedyskutowano obliczenia na podstawie nowych wzorów dla fali impulsowej i uderzeniowej. Wzory zgadzają się z klasycznymi w wypadku fal okresowych.
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Fluctuation-enhanced sensing: electronic dog nose identifies odors and counts molecules.
PublicationPrzedstawiono koncepcję wykrywania mieszanin gazów za pomocą analizy fluktuacji rezystancji sensora gazu. Porównano proponowaną ideę do wykorzystywanej w naturze przez zmysł węchu, w którym do mózgu dociera szereg pojedynczych impulsów elektrycznych wywołujących odczuwane wrażenie zapachowe.
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Noninvasive glucose sensing in scattering media using OCT, PAS, and TOF techniques.
PublicationW pracy przedstawiono możliwości wykorzystania optycznej tomografii koherencyjnej (OCT), spektroskopii fotoakustycznej (PAS)i spektroskopii czasu przelotu (TOF) w pomiarach glukozy w ośrodku silnie rozpraszającym. Równolegle opracowano modele propagacji światła w tych ośrodkach wykorzystując metodę Monte Carlo. W pomiarach wykorzystano ''Intralipid'' jako fantom tkanki. W dalszych badaniach wykorzystano mięso wieprzowe i dokonano...
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Comprehensive modernization of local heating system using cogeneration and renewable energy sources
PublicationPrzedstawiono przeprowadzoną kompleksową modernizację lokalnego systemu grzewczego z wprowadzeniem gospodarki cieplno-elektrycznej opartej na paliwie gazowym LNG, oraz z zastosowaniem odnawialnych źródeł energii w posatci energii słónecznej i geotermicznej.
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Concept for interpretation and assessment of slide bearings operation in Diesel enfines in probabilistic approach
PublicationW artykule zaproponowano interpretację wartościującą działania, które (podobnie jak przedstawione w mechanice klasycznej działania Hamiltona i Maupertiusa oraz działanie wynikające ze zmiany pędu ciała) jest rozpatrywane jako wielkość fizyczna o jednostce miary zwanej''dżulosekundą''. Przedstawiono propozycję ilościowej interpretacji działania dowolnego poprzecznego łożyska ślizgowego, w którym zachodzą oddziaływania energetyczne...
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Klocki samopompujące w łożyskach hydrodynamicznych = Self-pumping pads in the hydrodynamic bearings
PublicationWe współpracy z firmą ALSTOM HYDRO (Szwajcaria), zespół Katedry Konstrukcji i Eksploatacji Maszyn Politechniki Gdańskiej przeprowadził symulacje przepływowe kilku rozwiązań konstrukcyjnych mających na celu zwiększenie niezawodności turbin wodnych. W artykule opisano jedno z takich rozwiązań - tak zwane łożysko z klockami samopompującymi. Głównym celem jest uzyskanie przepływu oleju w układzie smarowania łożyska hydrodynamicznego...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublicationThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublicationIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
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Leading with Understanding: Cultivating Positive Relationships between Neurotypical Leaders and Neurodivergent Employees
PublicationNeurodivergent employees have atypical needs that require distinctive leadership approaches. In this study, the specific nature of a relationship between neurodivergent employees and their neurotypical leaders is explored through the lens of the Leader-Member-Exchange (LMX) theory. This two-phased qualitative study builds on 12 semi-structured interviews with neurodivergent employees and an unstructured focus group with 15 individuals...
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BACTERIAL INACTIVATION VIA LASER-DRIVEN GOLD NANOPARTICLE HEATING: SIMULATION AND ANALYSIS
PublicationThis study utilizes CFD technique to simulate the inactivation of E. coli bacteria within a microfluidic chamber, employing gold nanoparticles irradiated by a laser beam. Employing a single-phase model, the presence of bacteria is considered by treating thermal properties in the governing equations as effective, combining those of water and bacteria using established correlations from scientific literature. The conversion of light...
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Inverse surrogate modeling for low-cost geometry scaling of microwave and antenna structures
PublicationPurpose–The purpose of this paper is to investigate strategies for expedited dimension scaling ofelectromagnetic (EM)-simulated microwave and antenna structures, exploiting the concept of variable-fidelity inverse surrogate modeling.Design/methodology/approach–A fast inverse surrogate modeling technique is described fordimension scaling of microwave and antenna structures. The model is established using referencedesigns obtained...
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Modern remote sensing and the challenges facing education systems in terms of its teaching
PublicationCurrently the fastest growing area of geodesy is undoubtedly remote sensing. The importance that it has recently conducted on the effectiveness of worldwide research determines its huge success. Examination of the specific characteristics of objects without direct contact with them is a key feature has opened the way to the new very interesting areas of contemporary research. In this light, it seems reasonable to say that there...
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Current based Normalized Triple Covariance as a bearings diagnostic feature in induction motor
PublicationDiagnosis of induction motors, conducted remotely by measuring and analyzing the supply current is attractive with the lack of access to the engine. So far there is no solution, based on analysis of current, the credibility of which allow use in industry. Statistics of IM bearing failures of induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is so important. The article provides...
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Rapid Microwave Design Optimization in Frequency Domain Using Adaptive Response Scaling
PublicationIn this paper, a novel methodology for cost-efficient microwave design optimization in the frequency domain is proposed. Our technique, referred to as adaptive response scaling (ARS), has been developed for constructing a fast replacement model (surrogate) of the high-fidelity electromagnetic-simulated model of the microwave structure under design using its equivalent circuit (low-fidelity model). The basic principle of ARS is...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Coastline change-detection method using remote sensing satellite observation data
PublicationCoastal zones are not only the fundaments for local economics based on trade, shipping and transport services, but also a source of food, energy and resources. Apart from offering diverse opportunities for recreation and tourism, coastal zones provide protection against storms and other meteorological disturbances. Environmental information is also essential because of the direct influence on a country’s maritime zones, which are...
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Inverse surrogate models for fast geometry scaling of miniaturized dual-band couplers
PublicationRe-design of microwave structures for various sets of performance specifications is a challenging task, particularly for compact components where considerable electromagnetic (EM) cross-couplings make the relationships between geometry parameters and the structure responses complex. Here, we address geometry scaling of miniaturized dual-band couplers by means of inverse surrogate modeling. Our approach allows for fast estimation...
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OPERATING CONDITIONS OF SLIDE BEARINGS OF MILLS USED IN KGHM POLSKA MIEDŹ S.A.
PublicationThe paper contains the results from a tec hnical analysis of the conditions of the operation of hydrodynamic bearings supporting the drums of ore processing mills at KGHM Polska Mied ź S.A. A theoretical analysis was performed on the grounds of onsite examination and measurem ents of principal dimensions of the bearings of interest. The computer simulation covered the characteristics of the oil film in the bearings...
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Recurrent potential pulse technique for improvement of glucose sensing ability of 3D polypyrrole
PublicationIn this work, a new approach for using a 3D polypyrrole (PPy) conducting polymer as a sensing material for glucose detection is proposed. Polypyrrole is electrochemically polymerized on a platinum screen-printed electrode in an aqueous solution of lithium perchlorate and pyrrole. PPy exhibits a high electroactive surface area and high electrochemical stability, which results in it having excellent electrocatalytic properties. The...
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A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems
PublicationIn this chapter, the authors propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...
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Innovative e-learning approach in teaching based on case studies - Innocase project
PublicationThe article presents the application of innovative e-learning approach for the creation of case study content. Case study methodology is becoming more and more widely applied in modern education, especially in business and management field. Although case study methodology is quite well recognized and used in education, there are still few examples of developing e-learning content on the basis of case studies. This task is to be...
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Merging extremum seeking and self-optimizing narrowband interference canceller - overdetermined case
PublicationActive cancellation systems rely on destructive interference to achieve rejection of unwanted disturbances entering the system of interest. Typical practical applications of this method employ a simple single input, single output arrangement. However, when a spatial wavefield (e.g. acoustic noise or vibration) needs to be controlled, multichannel active cancellation systems arise naturally. Among these, the so-called overdetermined...
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Exploring the factor structure and the validity of the abbreviated Basic and Earning Self-Esteem Scales
PublicationThe original longer versions (Forsman & Johnson, 1996) and abbreviated versions of the Basic and Earning Self-Esteem Scales have been used in clinical and non-clinical settings, but little is known about the factor structure and the validity of these scales in their abbreviated forms. The original longer versions of the scales comprise several dimensions, but both abbreviated versions of the scales have been interpreted as if they...
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THE ONLINE APPLICATION AND E-LEARNING IN THE COMPETENCE-BASED MANAGEMENT IN PUBLIC ADMINISTRATION ORGANIZATIONS
PublicationThe integration of effective management of work-related processes and utilization of human resources potential leads to the development of organization. The purpose of this paper was to examine how the principles of competences-based management can be introduced to enhance organization’s effectiveness in human resources management. A model of assessment and development of competences-based management, embracing an online application...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Water-Lubricated Journal Bearings Marine Applications, Design, and Operational Problems and Solutions
PublicationWater-Lubricated Journal Bearings: Marine Applications, Design, and Operational Problems and Solutions provides cutting-edge design solutions, common problems and methods for avoiding them, and material selection considerations for the use of water-lubricated journal bearings in marine environments. These bearings have many advantages, including the absence of the potential for oil contamination. They are also sensitive, and their...
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Enhanced gas sensing by graphene-silicon Schottky diodes under UV irradiation
PublicationThe effect of ultraviolet (UV) or blue irradiation on graphene/n-doped silicon Schottky junctions toward gas sensing was investigated. Schottky diodes were subjected to oxidizing nitrogen dioxide (NO2, 1–3 ppm) and reducing tetrahydrofuran (THF, 50–200 ppm), showing significantly different responses observed on the currentvoltage (I-V) characteristics, especially under UV light (275 nm). NO2 affected the resistive part of the forward region...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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Nonlinearity shaping in nanostructured glass-diamond hybrid materials for optical fiber preforms
PublicationNanodiamond integration with optical fibers has proved a compelling methodology for magneto-optics. We reveal that the applicability of nanodiamonds in nonlinear optics goes beyond the previous demonstrations of frequency converters. Instead, we exploit the recently reported volumetric integration of nanodiamonds along the optical fiber core and show that the nonlinear response of glasses can be manipulated by nanodiamonds. By...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublicationCoding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublicationOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublicationPurpose – This paper proposes a research model in which learning goal orientation (LGO) mediates the impacts of relational capital and psychological capital (PsyCap) on work engagement. Design/methodology/approach – Data obtained from 475 managers and employees in the manufacturing and service industries in Poland were utilized to assess the linkages given above. Common method variance was controlled by the unmeasured latent method...
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Environmental impact of construction. Methods of conscious shaping architecture in terms of ecological solutions
PublicationShaping an ecologically conscious society is a process that also affects architecture. Currently, designers are eagerly looking for solutions that are beneficial in terms of carbon footprint. For the proper multi-criteria assessment and selection of adequate solutions, it is necessary to use appropriate tools such as, for example, the Life Cycle Assessment (LCA) method or the rules of ecological certification (BREEAM and LEED)....
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Impact of temperature on optical sensing in biology based on investigation of SARS‐CoV ‐2
PublicationIn this paper, we present an investigation of the influence of the temperature on the sensing of biological samples. We used biofunctionalized microsphere-based fiber-optic sensor to detect immunoglobulin G attached to the sensor head at temperatures relevant in biological research: 5°C, 25°C, and 55°C. The construction of the sensor allowed us to perform measurements in the small amount of solution. The results of our experiment...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...