Roberto Todeschini
YOU?
Author Swipe
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: 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: 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: Identification of Photodegradation Products of Escitalopram in Surface Water by HPLC-MS/MS and Preliminary Characterization of Their Potential Impact on the Environment
Identification of Photodegradation Products of Escitalopram in Surface Water by HPLC-MS/MS and Preliminary Characterization of Their Potential Impact on the Environment Open
The study concerns the photodegradation of the antidepressant escitalopram (ESC), the S-enantiomer of the citalopram raceme, both in ultrapure and surface water, considering the contribution of indirect photolysis through the presence of n…
View article: Multi-Task Neural Networks and Molecular Fingerprints to Enhance Compound Identification from LC-MS/MS Data
Multi-Task Neural Networks and Molecular Fingerprints to Enhance Compound Identification from LC-MS/MS Data Open
Mass spectrometry (MS) is widely used for the identification of chemical compounds by matching the experimentally acquired mass spectrum against a database of reference spectra. However, this approach suffers from a limited coverage of the…
View article: Parsimonious Optimization of Multitask Neural Network Hyperparameters
Parsimonious Optimization of Multitask Neural Network Hyperparameters Open
Neural networks are rapidly gaining popularity in chemical modeling and Quantitative Structure–Activity Relationship (QSAR) thanks to their ability to handle multitask problems. However, outcomes of neural networks depend on the tuning of …
View article: Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite
Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite Open
In this article, the “ Acknowledgments ” section was missing the text below: H.C., D.P.R., and H.Z. at Rutgers University at Camden were partially supported by the NIEHS (grants R01ES031080 and R15ES023148).The authors regret the error.
View article: Nuclear receptor modulators: Catching information by machine learning
Nuclear receptor modulators: Catching information by machine learning Open
Nuclear receptors (NRs) are involved in fundamental human health processes and are a relevant target for toxicological risk assessment. To help prioritize chemicals that can mimic natural hormones and be endocrine disruptors, computational…
View article: Nuclear receptor modulators: Catching information by machine learning
Nuclear receptor modulators: Catching information by machine learning Open
Nuclear receptors (NRs) are involved in fundamental human health processes and are a relevant target for toxicological risk assessment. To help prioritize chemicals that can mimic natural hormones and be endocrine disruptors, computational…
View article: CATMoS: Collaborative Acute Toxicity Modeling Suite
CATMoS: Collaborative Acute Toxicity Modeling Suite Open
BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk …
View article: Evaluation of classification performances of minimum spanning trees by 13 different metrics
Evaluation of classification performances of minimum spanning trees by 13 different metrics Open
Minimum Spanning Tree (MST) is a well-known clustering algorithm that provides a graphical tree representation of the objects in a data set by exploiting local information to link each pair of similar objects. The a-posteriori analysis of …
View article: Predicting molecular activity on nuclear receptors by multitask neural networks
Predicting molecular activity on nuclear receptors by multitask neural networks Open
The interest in multitask and deep learning strategies has been increasing in the last few years, in application to large and complex dataset for quantitative structure‐activity relationship (QSAR) analysis. Multitask approaches allow the …
View article: QSAR Modeling: Where Have You Been? Where Are You Going To?
QSAR Modeling: Where Have You Been? Where Are You Going To? Open
Quantitative Structure-Activity Relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limita…
View article: Data for: Deep Ranking Analysis by Power Eigenvectors (DRAPE): a polypharmacology case study
Data for: Deep Ranking Analysis by Power Eigenvectors (DRAPE): a polypharmacology case study Open
A dataset comprising 55 molecules described by seven criteria was used. The criteria are composed of binding activity values for each target expressed as half maximal activity concentration (AC50), based on the dose-response curves, thus t…
View article: CERAPP: Collaborative Estrogen Receptor Activity Prediction Project
CERAPP: Collaborative Estrogen Receptor Activity Prediction Project Open
BACKGROUND: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested …
View article: CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity
CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity Open
The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applica…
View article: Similarity/Diversity Indices on Incidence Matrices Containing Missing Values
Similarity/Diversity Indices on Incidence Matrices Containing Missing Values Open
Quantifying the diversity content of an incidence matrix is challenging in several scientific fields. The existing indices capture diverse facets of diversity and thus comparing their behaviour is not a straightforward task. For example, a…
View article: Publisher Correction: Scaffold hopping from natural products to synthetic mimetics by holistic molecular similarity
Publisher Correction: Scaffold hopping from natural products to synthetic mimetics by holistic molecular similarity Open
The original PDF and HTML versions of this Article contained errors in Eqs. (4) and (6). In Eq. (4), the not equal symbol displayed incorrectly as #, and in Eq. (6), the greater than symbol was displayed in place of the less than symbol. T…
View article: A QSTR-Based Expert System to Predict Sweetness of Molecules
A QSTR-Based Expert System to Predict Sweetness of Molecules Open
This work describes a novel approach based on advanced molecular similarity to predict the sweetness of chemicals. The proposed Quantitative Structure-Taste Relationship (QSTR) model is an expert system developed keeping in mind the five p…
View article: Data Analysis in Chemistry and Bio-Medical Sciences
Data Analysis in Chemistry and Bio-Medical Sciences Open
There is an increasing necessity for multidisciplinary collaborations in molecular science between experimentalists and theoretical scientists, as well as among theoretical scientists from different fields.[...]