| Nome |
# |
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Mixtures, metabolites, ionic liquids: a new measure to evaluate similarity between complex chemical systems, file e39773b3-5151-35a3-e053-3a05fe0aac26
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216
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Defining a novel k-nearest neighbours approach to assess the applicability domain of a QSAR model for reliable predictions, file e39773b1-d238-35a3-e053-3a05fe0aac26
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183
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Comparison of Different Approaches to Define the Applicability Domain of QSAR Models, file e39773b1-bd45-35a3-e053-3a05fe0aac26
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149
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Consensus versus Individual QSARs in Classification: Comparison on a Large-Scale Case Study, file e39773b6-11b1-35a3-e053-3a05fe0aac26
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137
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A QSTR-based expert system to predict sweetness of molecules, file e39773b7-9308-35a3-e053-3a05fe0aac26
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79
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Expanding Antineoplastic Drugs Surface Monitoring Profiles: Enhancing of Zwitterionic Hydrophilic Interaction Methods, file e39773b8-9269-35a3-e053-3a05fe0aac26
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40
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Nuclear receptor modulators: Catching information by machine learning, file e39773b7-dde7-35a3-e053-3a05fe0aac26
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39
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A New Similarity/Diversity Measure for the Characterization of DNA Sequences, file e39773b1-31fe-35a3-e053-3a05fe0aac26
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35
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From the Streets to the Judicial Evidence: Determination of Traditional Illicit Substances in Drug Seizures by a Rapid and Sensitive UHPLC-MS/MS-Based Platform, file 57caae10-1086-4c83-b92f-9778c73681e8
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31
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Condensed Phase Membrane Introduction Mass Spectrometry: A Direct Alternative to Fully Exploit the Mass Spectrometry Potential in Environmental Sample Analysis, file 920139e2-cb30-4b35-bc6c-6469e5a518c4
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27
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Identification of Photodegradation Products of Escitalopram in Surface Water by HPLC-MS/MS and Preliminary Characterization of Their Potential Impact on the Environment, file 808d9c6b-b585-4e79-ae9a-7704619ed2b6
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23
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Chemical profiling and multivariate data fusion methods for the identification of the botanical origin of honey, file e39773b9-7d3a-35a3-e053-3a05fe0aac26
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22
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Multi-Task Neural Networks and Molecular Fingerprints to Enhance Compound Identification from LC-MS/MS Data, file 515ca061-77c7-4c88-b8b5-8c41fbf3f370
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18
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Artificial Intelligence and Machine Learning Methods to Evaluate Cardiotoxicity following the Adverse Outcome Pathway Frameworks, file 105cb4b8-c773-415c-8982-043f26ab5801
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15
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Enhanced Visualization and Interpretation of XMCD-PEEM Data Using SOM-RPM Machine Learning, file df65f172-f082-4252-ab26-d9683c320ff1
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15
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Exploring the Relationship between Polymer Surface Chemistry and Bacterial Attachment Using ToF-SIMS and Self-Organizing maps, file 1d9e211d-97b8-4191-b332-a6d1f7b8b019
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10
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Chemical profiling and multivariate data fusion methods for the identification of the botanical origin of honey, file e39773b8-514b-35a3-e053-3a05fe0aac26
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8
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Effect of data preprocessing and machine learning hyperparameters on mass spectrometry imaging models, file 4ae500a4-ee3d-4e83-b46a-3fe5031f2786
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6
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Kernel-based mapping of reliability in predictions for consensus modelling, file b8aaa772-c8ac-40a7-a9e2-9bed42ebdb66
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6
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Analyzing 3D hyperspectral TOF-SIMS depth profile data using self-organizing map-relational perspective mapping, file e39773b6-eb5a-35a3-e053-3a05fe0aac26
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6
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Comparison of machine learning approaches for the classification of elution profiles, file 3600d713-d9de-4562-81ed-e8757effc832
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5
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Particle size, chemical composition, seasons of the year and urban, rural or remote site origins as determinants of biological effects of particulate matter on pulmonary cells, file e39773b3-6647-35a3-e053-3a05fe0aac26
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5
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Valorization of side streams from a SSF biorefinery plant: Wheat straw lignin purification study, file e39773b3-9d25-35a3-e053-3a05fe0aac26
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5
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Structural alerts for the identification of bioaccumulative compounds, file e39773b4-e196-35a3-e053-3a05fe0aac26
|
4
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Improving bitter pit prediction by the use of X-ray fluorescence (XRF): A new approach by multivariate classification, file 58d403d6-527b-41f7-9884-6e914db38967
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3
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High-level data fusion: perspectives in QSAR and analytical applications, file e39773b3-f63b-35a3-e053-3a05fe0aac26
|
3
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A Dynamic MOLMAP approach for pattern classification in three-way data, file e39773b4-ba2b-35a3-e053-3a05fe0aac26
|
3
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Classification-based Machine Learning Approaches to Predict the Taste of Molecules: A Review, file 3a182869-86da-4e6c-8e12-793f56f38e8c
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2
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Effectiveness of molecular fingerprints for exploring the chemical space of natural products, file 4d8418b4-8cc7-4373-a806-fb6861e6e909
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2
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Characterization of pyrite weathering products by Raman hyperspectral imaging and chemometrics techniques, file 85e4b225-8ad9-446b-9148-269bd43b482a
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2
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Response Surface Methodology Approach to Evaluate the Effect of Transition Metals and Oxygen on Photo-Degradation of Methionine in a Model Wine System Containing Riboflavin, file c532f222-c6e5-4f5d-9c1d-7d587c585603
|
2
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N3 and BNN: two new similarity based classification methods in comparison with other classifiers, file e39773b2-c595-35a3-e053-3a05fe0aac26
|
2
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Recent advances in consensus modelling of multiple analytical chemical data, file e39773b2-c9a2-35a3-e053-3a05fe0aac26
|
2
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A MATLAB toolbox for Principal Component Analysis and unsupervised exploration of data structure, file e39773b2-de50-35a3-e053-3a05fe0aac26
|
2
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Beware of Unreliable Q2! A Comparative Study of Regression Metrics for Predictivity Assessment of QSAR Models, file e39773b3-5171-35a3-e053-3a05fe0aac26
|
2
|
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Mixtures, metabolites, ionic liquids: a new measure to evaluate similarity between complex chemical systems. In Abstract book of the 21st EuroQSAR, file e39773b3-58b2-35a3-e053-3a05fe0aac26
|
2
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High-level data fusion: perspectives in QSAR and analytical applications, file e39773b3-fb01-35a3-e053-3a05fe0aac26
|
2
|
|
High-level data fusion: perspectives in QSAR and analytical applications, file e39773b3-fb02-35a3-e053-3a05fe0aac26
|
2
|
|
Structural alerts for the identification of bioaccumulative compounds, file e39773b4-e194-35a3-e053-3a05fe0aac26
|
2
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Detecting activity-rich structural regions by a new chemoinformatic approach: Mapping of Activity through Dichotomic Scores (MADS), file e39773b4-e4d6-35a3-e053-3a05fe0aac26
|
2
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Detecting activity-rich structural regions by a new chemoinformatic approach: Mapping of Activity through Dichotomic Scores (MADS), file e39773b4-e4d7-35a3-e053-3a05fe0aac26
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2
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QSAR models to predict Acute Oral Systemic Toxicity, file e39773b4-e4e2-35a3-e053-3a05fe0aac26
|
2
|
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Multivariate classification of Chianti red wines based on massive sampling and ICP-MS element composition, file e39773b4-fe19-35a3-e053-3a05fe0aac26
|
2
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Consensus Prediction of Androgen Receptor Activity within the CoMPARA Project, file e39773b5-740b-35a3-e053-3a05fe0aac26
|
2
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|
Recent Advances in High-Level Fusion Methods to Classify Multiple Analytical Chemical Data, file e39773b5-b730-35a3-e053-3a05fe0aac26
|
2
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|
A new concept of higher-order similarity and the role of distance/similarity measures in local classification methods, file e39773b8-4d17-35a3-e053-3a05fe0aac26
|
2
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Sviluppo di un metodo veloce, economico e non distruttivo per la quantificazione della componente ionica nel particolato atmosferico, file e39773b2-381d-35a3-e053-3a05fe0aac26
|
1
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A novel unsupervised method for reducing the dimensionality of large QSAR datasets., file e39773b2-3d7d-35a3-e053-3a05fe0aac26
|
1
|
|
Comparison of approaches to define Applicability Domain for the application of QSAR models, file e39773b2-4351-35a3-e053-3a05fe0aac26
|
1
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Local models for the prediction of acute toxicity to Daphnia magna, file e39773b2-5d0a-35a3-e053-3a05fe0aac26
|
1
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Recent advancements to define the applicability domain of qsar models, file e39773b2-63d7-35a3-e053-3a05fe0aac26
|
1
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K-contractive map (k-cm) for classification, file e39773b2-65b0-35a3-e053-3a05fe0aac26
|
1
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Uso de relaciones diagnostico, biomarcadores y redes neurales de Kohonen de 3 vias para la monitorizacion de la evolution temporal de los vertidos de petroleo, file e39773b2-9f17-35a3-e053-3a05fe0aac26
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1
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Recent advances in consensus modelling of multiple analytical chemical data, file e39773b2-b3a1-35a3-e053-3a05fe0aac26
|
1
|
|
N3 and BNN: two new similarity based classification methods in comparison with other classifiers, file e39773b2-b5c4-35a3-e053-3a05fe0aac26
|
1
|
|
Quantitative structure–activity relationships to predict sweet and non-sweet tastes, file e39773b3-19aa-35a3-e053-3a05fe0aac26
|
1
|
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Integration of QSAR ready biodegradability predictions by means of qualitative consensus, file e39773b3-5a85-35a3-e053-3a05fe0aac26
|
1
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Exploiting the potential of molecular descriptors through data-fusion strategies: A case study on Cytochrome P450, file e39773b3-5a88-35a3-e053-3a05fe0aac26
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1
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Data integration to increase quality and reliability of QSAR predictions., file e39773b3-cd23-35a3-e053-3a05fe0aac26
|
1
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NON LINEAR CLASSIFICATION OF COMMERCIAL MEXICAN TEQUILAS, file e39773b3-f3d1-35a3-e053-3a05fe0aac26
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1
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NON LINEAR CLASSIFICATION OF COMMERCIAL MEXICAN TEQUILAS, file e39773b3-f833-35a3-e053-3a05fe0aac26
|
1
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QSAR models to predict properties of dyes for regulatory use, file e39773b4-e127-35a3-e053-3a05fe0aac26
|
1
|
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QSAR models to predict properties of dyes for regulatory use, file e39773b4-e128-35a3-e053-3a05fe0aac26
|
1
|
|
Structural alerts for the identification of bioaccumulative compounds, file e39773b4-e195-35a3-e053-3a05fe0aac26
|
1
|
|
QSAR models to predict Acute Oral Systemic Toxicity, file e39773b4-e4e0-35a3-e053-3a05fe0aac26
|
1
|
|
QSAR models to predict properties of dyes for regulatory use, file e39773b4-ea32-35a3-e053-3a05fe0aac26
|
1
|
|
Detecting activity-rich structural regions by a new chemoinformatic approach: Mapping of Activity through Dichotomic Scores (MADS), file e39773b4-ea34-35a3-e053-3a05fe0aac26
|
1
|
|
Capsaicinoids in Chili Habanero by Flow Injection with Coulometric Array Detection, file e39773b5-a904-35a3-e053-3a05fe0aac26
|
1
|
|
Deep Ranking Analysis by Power Eigenvectors (DRAPE): A wizard for ranking and multi-criteria decision making, file e39773b5-d6b7-35a3-e053-3a05fe0aac26
|
1
|
|
Self-Organizing Map and Relational Perspective Mapping for the Accurate Visualization of High-Dimensional Hyperspectral Data, file e39773b6-7007-35a3-e053-3a05fe0aac26
|
1
|
|
ToF-SIMS and Machine Learning for Single-Pixel Molecular Discrimination of an Acrylate Polymer Microarray, file e39773b6-aeda-35a3-e053-3a05fe0aac26
|
1
|
|
Diabetes mellitus type 2: Exploratory data analysis based on clinical reading, file e39773b6-ba2c-35a3-e053-3a05fe0aac26
|
1
|
|
NURA: A curated dataset of nuclear receptor modulators, file e39773b7-1d35-35a3-e053-3a05fe0aac26
|
1
|
|
Traceability of soybeans produced in Argentina based on their trace element profiles, file e39773b7-3237-35a3-e053-3a05fe0aac26
|
1
|
|
A similarity-based QSAR model for predicting acute toxicity towards the fathead minnow (Pimephales promelas), file e39773b8-4d2a-35a3-e053-3a05fe0aac26
|
1
|
|
A MATLAB toolbox for Principal Component Analysis and unsupervised exploration of data structure, file e39773b8-514a-35a3-e053-3a05fe0aac26
|
1
|
|
Multivariate comparison of classification performance measures, file e39773b8-534b-35a3-e053-3a05fe0aac26
|
1
|
|
Beware of Unreliable Q2! A Comparative Study of Regression Metrics for Predictivity Assessment of QSAR Models, file e39773b8-534c-35a3-e053-3a05fe0aac26
|
1
|
| Totale |
1.163 |
