Davide Boldini
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View article: Machine Learning-Driven Data Valuation for Optimizing High-Throughput Screening Pipelines
Machine Learning-Driven Data Valuation for Optimizing High-Throughput Screening Pipelines Open
In the rapidly evolving field of drug discovery, high-throughput screening (HTS) is essential for identifying bioactive compounds. This study introduces a novel application of data valuation, a concept for evaluating the importance of data…
View article: Barlow Twins Deep Neural Network for Advanced 1D Drug-Target Interaction Prediction
Barlow Twins Deep Neural Network for Advanced 1D Drug-Target Interaction Prediction Open
Accurate prediction of drug-target interactions is critical for advancing drug discovery. By reducing time and cost, machine learning and deep learning can accelerate this laborious discovery process. In a novel approach, BarlowDTI, we uti…
View article: Synergizing Chemical Structures and Bioassay Descriptions for Enhanced Molecular Property Prediction in Drug Discovery
Synergizing Chemical Structures and Bioassay Descriptions for Enhanced Molecular Property Prediction in Drug Discovery Open
The precise prediction of molecular properties can greatly accelerate the development of new drugs. However, in silico molecular property prediction approaches have been limited so far to assays for which large amounts of data are availabl…
View article: Effectiveness of molecular fingerprints for exploring the chemical space of natural products
Effectiveness of molecular fingerprints for exploring the chemical space of natural products Open
Natural products are a diverse class of compounds with promising biological properties, such as high potency and excellent selectivity. However, they have different structural motifs than typical drug-like compounds, e.g. , a wider range o…
View article: Machine Learning Assisted Hit Prioritization for High Throughput Screening in Drug Discovery
Machine Learning Assisted Hit Prioritization for High Throughput Screening in Drug Discovery Open
Efficient prioritization of bioactive compounds from high throughput screening campaigns is a fundamental challenge for accelerating drug development efforts. In this study, we present the first data-driven approach to simultaneously detec…
View article: TwinBooster: Synergising Large Language Models with Barlow Twins and Gradient Boosting for Enhanced Molecular Property Prediction
TwinBooster: Synergising Large Language Models with Barlow Twins and Gradient Boosting for Enhanced Molecular Property Prediction Open
The success of drug discovery and development relies on the precise prediction of molecular activities and properties. While in silico molecular property prediction has shown remarkable potential, its use has been limited so far to assays …
View article: Effectiveness of molecular fingerprints for exploring the chemical space of natural products
Effectiveness of molecular fingerprints for exploring the chemical space of natural products Open
Natural products are a diverse class of compounds with promising biological properties, such as high potency and excellent selectivity. However, they have different structural motifs than typical drug-like compounds, e.g., a wider range of…
View article: Data Valuation: A novel approach for analyzing high throughput screen data using machine learning
Data Valuation: A novel approach for analyzing high throughput screen data using machine learning Open
In the rapidly evolving field of drug discovery, High Throughput Screening (HTS) is a pivotal technique for identifying promising compounds. Despite its wide usage, the primary challenge remains in efficiently sifting through vast chemical…
View article: Machine learning assisted hit prioritization for high throughput screening in drug discovery
Machine learning assisted hit prioritization for high throughput screening in drug discovery Open
Efficient prioritization of bioactive compounds from high throughput screening campaigns is a fundamental challenge for accelerating drug development efforts. In this study, we present the first data-driven approach to simultaneously detec…
View article: Effectiveness of molecular fingerprints for exploring the chemical space of natural products
Effectiveness of molecular fingerprints for exploring the chemical space of natural products Open
Natural products are a diverse class of compounds with promising biological properties, such as high potency and excellent selectivity. However, they have different structural motifs than typical drug-like compounds, e.g., a wider range of…
View article: Tuning gradient boosting for imbalanced bioassay modelling with custom loss functions
Tuning gradient boosting for imbalanced bioassay modelling with custom loss functions Open
While in the last years there has been a dramatic increase in the number of available bioassay datasets, many of them suffer from extremely imbalanced distribution between active and inactive compounds. Thus, there is an urgent need for no…