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13 papers · ranked by Valyu relevance

01
CchemRxiv10 Mar 2022
Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels
Ping Yang, E. Adrian Henle, Xiaoli Fern, Cory M. Simon
Pesticides benefit agriculture by increasing crop yield, quality, and security. However, pesticides may inadvertently harm bees, which are agriculturally and ecologically vital as pollinators. The development of new pesticides---driven by pest resistance to and demands to reduce negative environmental impacts of…
74relevance
02
CchemRxiv8 Mar 2022
Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels
Ping Yang, E. Adrian Henle, Cory M. Simon, Xiaoli Fern
Pesticides benefit agriculture by increasing crop yield, quality, and security. However, pesticides may inadvertently harm bees, which are valuable as pollinators. Thus, candidate pesticides in development pipelines must be assessed for toxicity to bees. Leveraging a data set of 382 molecules with toxicity labels from…
74relevance
03
CchemRxiv12 Jan 2024
PythiaCHEM : a user-friendly machine learning toolkit for chemistry
Stamatia Zavitsanou, Zonghua Bo, Emanuele Casali, Matthew Langton + 1 more
Machine learning (ML) is currently transforming the field of chemistry by offering unparalleled efficiency in addressing complex challenges. Despite the progress made, a notable gap persists in the availability of user-friendly tools tailored to chemical problems involving small and sparse datasets. Here, we introduce…
69relevance
04
CchemRxiv3 Nov 2021
Naive Bayes classification model for isotopologue detection in LC-HRMS data
Denice van Herwerden, Jake O'Brien, Phil Choi, Kevin Thomas + 2 more
Isotopologue identification or removal is a necessary step to reduce the number of features that need to be identified in samples analyzed with non-targeted analysis. Currently available approaches rely on either predicted isotopic patterns or an arbitrary mass tolerance, requiring information on the molecular formula…
66relevance
05
CchemRxiv24 Aug 2022
Uncertainty Informed Screening for Safer Solvents used in the Synthesis of Perovskite Based Solar Cells via Machine Learning
Deepesh Giri, Arpan Mukherjee, Krishna Rajan
The objective of this paper is to do a multi-output binary classification for endocrine disrupting (ED) nature of solvents that are frequently used in the synthesis of perovskites. Information on such solvents is not readily available in the form of datasets, rather it is embedded in the literature, which forms an…
63relevance
06
CchemRxiv18 Oct 2022
Machine Learning Identification of Active Sites in Graphite-Conjugated Catalysts
Kunal Lodaya, Nathan Ricke, Kelly Chen, Troy Van Voorhis
Graphite-conjugated catalysts (GCCs) are a promising class of materials that combine many of the advantages of heterogenous and homogeneous catalysts. In particular, GCCs containing an aryl-pyridinium active site appear to be effective nonmetal catalysts for the oxygen reduction reaction (ORR). In this study, we…
63relevance
07
CchemRxiv24 Jun 2022
Data-driven multi-objective optimization tactics for catalytic asymmetric reactions
Jordan Dotson, Lucy van Dijk, Jacob Timmerman, Samantha Grosslight + 5 more
Optimization of catalyst structure to simultaneously improve multiple reaction objectives (e.g., yield, enantio-, and regioselectivity) remains a formidable challenge. Herein, we describe a machine learning workflow for the multi-objective optimization of catalytic reactions that employ chiral bisphosphine ligands.…
63relevance
08
CchemRxiv24 May 2023
Critical Assessment of pH-Dependent Lipophilic Profiles of Small Molecules for Drug Design: Which One Should We Use and In Which Cases?
William J. Zamora Ramírez, Esteban Bertsch Aguilar, Sebastián Suñer Sánchez, Silvana Pinheiro
- 1. 1. CBio3 Laboratory, School of Chemistry, University of Costa Rica, San Pedro, San José, Costa Rica - 2. 2. Laboratory of Computational Toxicology and Artificial Intelligence (LaToxCIA), Biological Testing Laboratory (LEBi), University of Costa Rica, San Pedro, San José, Costa Rica - 3. 3. Advanced Computing Lab…
62relevance
09
CchemRxiv8 Nov 2024
Odor Classification: Exploring Feature Performance and Imbalanced Data Learning Techniques
Authors not listed
This research delves into olfaction, a sensory modality that remains complex and inadequately understood. We aim to fill in two gaps in recent studies that attempted to use machine learning and deep learning approaches to predict human smell perception. The first one is that molecules are usually represented with…
61relevance
10
CchemRxiv5 Jun 2023
Critical Assessment of pH-Dependent Lipophilic Profiles of Small Molecules for Drug Design: Which One Should We Use and In Which Cases?
Esteban Bertsch Aguilar, Sebastián Suñer Sánchez, Silvana Pinheiro, William J. Zamora Ramírez
- 1. 1. CBio3 Laboratory, School of Chemistry, University of Costa Rica, San Pedro, San José, Costa Rica - 2. 2. Laboratory of Computational Toxicology and Artificial Intelligence (LaToxCIA), Biological Testing Laboratory (LEBi), University of Costa Rica, San Pedro, San José, Costa Rica - 3. 3. Advanced Computing Lab…
60relevance
11
CchemRxiv9 Jun 2025
A 2025 perspective on the role of machine learning in clinical proteomics
Authors not listed
Machine learning holds significant promise for accelerating biomarker discovery in clinical proteomics, yet its real-world impact remains limited by widespread methodological pitfalls and unrealistic expectations. In this perspective, we critically examine the integration of machine learning into clinical proteomics…
59relevance
12
CchemRxiv2 Jan 2024
Mapping inorganic crystal chemical space
Hyunsoo Park, Anthony Onwuli, Keith T. Butler, Aron Walsh
The combination of elements from the Periodic Table defines a vast chemical space. Only a small fraction of these combinations yield materials that occur naturally or are accessible synthetically. Here, we enumerate binary, ternary, and quaternary element combinations to produce an extensive library of over 10^10…
58relevance
13
CchemRxiv10 Oct 2022
From descriptors to intrinsic fish toxicity of chemicals: an alternative approach to chemical prioritization
Saer Samanipour, Jake O'Brien, Malcolm Reid, Kevin Thomas + 1 more
The European Chemicals Agency (ECHA) and US Environmental Protection Agency (EPA) have listed approximately 800k chemicals that must be further investigated for their potential environmental and/or human health risk. A significant number of these chemicals have large enough global volumes of consumption (e.g.…
55relevance

Results for binary classification

Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels

Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels

PythiaCHEM : a user-friendly machine learning toolkit for chemistry

Naive Bayes classification model for isotopologue detection in LC-HRMS data

Uncertainty Informed Screening for Safer Solvents used in the Synthesis of Perovskite Based Solar Cells via Machine Learning

Machine Learning Identification of Active Sites in Graphite-Conjugated Catalysts

Data-driven multi-objective optimization tactics for catalytic asymmetric reactions

Critical Assessment of pH-Dependent Lipophilic Profiles of Small Molecules for Drug Design: Which One Should We Use and In Which Cases?

Odor Classification: Exploring Feature Performance and Imbalanced Data Learning Techniques

Critical Assessment of pH-Dependent Lipophilic Profiles of Small Molecules for Drug Design: Which One Should We Use and In Which Cases?

A 2025 perspective on the role of machine learning in clinical proteomics

Mapping inorganic crystal chemical space

From descriptors to intrinsic fish toxicity of chemicals: an alternative approach to chemical prioritization

Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels

Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels

PythiaCHEM : a user-friendly machine learning toolkit for chemistry

Naive Bayes classification model for isotopologue detection in LC-HRMS data

Uncertainty Informed Screening for Safer Solvents used in the Synthesis of Perovskite Based Solar Cells via Machine Learning

Machine Learning Identification of Active Sites in Graphite-Conjugated Catalysts

Data-driven multi-objective optimization tactics for catalytic asymmetric reactions

Critical Assessment of pH-Dependent Lipophilic Profiles of Small Molecules for Drug Design: Which One Should We Use and In Which Cases?

Odor Classification: Exploring Feature Performance and Imbalanced Data Learning Techniques

Critical Assessment of pH-Dependent Lipophilic Profiles of Small Molecules for Drug Design: Which One Should We Use and In Which Cases?

A 2025 perspective on the role of machine learning in clinical proteomics

Mapping inorganic crystal chemical space

From descriptors to intrinsic fish toxicity of chemicals: an alternative approach to chemical prioritization