Chemaxon's second generation search engine is being improved in order to serve distributed searches. Short overview of the roadmap, other improvements.
Akos Tarcsay (ChemAxon): How fast is Chemaxon RDBMS Search?ChemAxon
Ákos' study aims to provide an overview of ChemAxon's different search engines and web services. A benchmark will be presented along with statistics on the performance of the different JChem engines.
Chemaxon EU UGM 2022 | Translating data to predictive modelsChemAxon
Biological, chemical, and physical properties of molecules are encoded in their molecular structure. The challenge lies in discovering the relationships between the structure of the molecular graphs and the measured activity. In this presentation, we introduce Chemaxon’s new product, the Trainer Engine. It is designed to streamline the workflow starting from input data containing measured activities until validated models are implemented for a wide audience.
In addition to summarizing our results obtained with various machine learning model training scenarios, our goal is to highlight the model inference aspects. Accordingly, we present an integration use case with Chemaxon’s Design Hub. Connecting these applications widens the range of information resources available for decision-making on compound series to enhance drug discovery pipelines.
Biological, chemical and physical properties of molecules are encoded in their molecular structure. The challenge lies in discovering the relationships between the molecular graphs and the measured activity. Where data is measured, collected and curated for a series of compounds there is an opportunity to find the hidden relationships.
Chemical structures come in various shapes and sizes, depending on the scientists or even algorithms that create them. Though variability may sometimes seem subtle to a trained chemist’s eyes, these can introduce inconsistencies that impair chemical search algorithms or model building. Structure normalization is a key component of any cheminformatics workflow with an often underestimated significance. Finding relationships between chemical structures and their measured properties primarily relies on the representation of the chemical matter. Variability of the calculated features and descriptors for these representations can influence data analysis and accuracy of the predictions. During the first part of the presentation we will present the effect of chemical normalization on investigating correlations and building predictive models.
The second part of the talk will incorporate the results of model building on 163 ChEMBL targets extracted from the bioactivity benchmark set1. Results with different descriptor generation methods including ECFP fingerprints, MACCS key, structural properties, geometry properties and phy-chem properties will be discussed in detail. This part focuses on summarizing the results of more than 3000 Random Forest models.
Finally model development for ADMET targets will be highlighted including hERG cardiotoxicity prediction, permeability and blood brain barrier penetration. We will describe how these models can be built, analyzed, optimized and deployed using our new machine learning platform.
Efficient biomolecular structural data handling and analysis - Webinar with D...ChemAxon
In this joint event our experts are coming together to elaborate on the technical and scientific opportunities coming from this partnership. If you are working on the discovery of next generation drugs and using structure-based approach in your research, join us to learn how to leverage vast biomolecular structural data with innovative technologies.
Chemaxon is a software and services provider founded in 1998 with headquarters in Budapest and around 250 employees worldwide. Their software supports drug discovery workflows from target identification through clinical trials. They provide tools for biomolecule data management to help with challenges like understanding biological context across teams and preventing data silos. Their software allows users to model, register, standardize, visualize, and design complex biomolecules like peptides, oligonucleotides, conjugates, proteins and antibodies to facilitate collaboration in biotherapeutic fields.
Cheminfo Stories 2021 | Virtual UGM | Marvin Pro: The first releaseChemAxon
Marvin Pro is a new web-based chemical editor capable of drawing large synthesis schemes and biomolecules in publication quality. It can be extended with other modules and integrated with ChemAxon and third-party products. Some key features include impeccable visual quality matching journal styles, fast drawing using keyboard shortcuts, and chemical understanding for clean 2D structures and properties display. An alpha version is available on the Chemicalize website and the developers welcome feedback to help perfect the tool.
This document discusses enhanced stereochemistry representation in molecular structures, including absolute, and, and or labels. It explains that absolute labels indicate known exact stereochemistry, and labels indicate mixtures. Or labels signify a pure but unknown structure, while and labels represent mixtures where both configurations are present. Examples are given to illustrate how these labels can be used to define stereochemical mixtures and unknown structures. The document also demonstrates how chromatographic separation can be used to separate stereoisomer mixtures into pure components.
Intellectual property (IP) intelligence solutions designed for the way resear...ChemAxon
Leveraging IP intelligence through the researcher workflow requires the curation of chemistry patents including many thousands of molecules. This complex task is time-consuming and error-prone when done manually, whereas using ChemAxon’s ChemCuratora to analyze and extract chemical information in patents and other documents means the process can be done accurately in a fraction of the time.
Akos Tarcsay (ChemAxon): How fast is Chemaxon RDBMS Search?ChemAxon
Ákos' study aims to provide an overview of ChemAxon's different search engines and web services. A benchmark will be presented along with statistics on the performance of the different JChem engines.
Chemaxon EU UGM 2022 | Translating data to predictive modelsChemAxon
Biological, chemical, and physical properties of molecules are encoded in their molecular structure. The challenge lies in discovering the relationships between the structure of the molecular graphs and the measured activity. In this presentation, we introduce Chemaxon’s new product, the Trainer Engine. It is designed to streamline the workflow starting from input data containing measured activities until validated models are implemented for a wide audience.
In addition to summarizing our results obtained with various machine learning model training scenarios, our goal is to highlight the model inference aspects. Accordingly, we present an integration use case with Chemaxon’s Design Hub. Connecting these applications widens the range of information resources available for decision-making on compound series to enhance drug discovery pipelines.
Biological, chemical and physical properties of molecules are encoded in their molecular structure. The challenge lies in discovering the relationships between the molecular graphs and the measured activity. Where data is measured, collected and curated for a series of compounds there is an opportunity to find the hidden relationships.
Chemical structures come in various shapes and sizes, depending on the scientists or even algorithms that create them. Though variability may sometimes seem subtle to a trained chemist’s eyes, these can introduce inconsistencies that impair chemical search algorithms or model building. Structure normalization is a key component of any cheminformatics workflow with an often underestimated significance. Finding relationships between chemical structures and their measured properties primarily relies on the representation of the chemical matter. Variability of the calculated features and descriptors for these representations can influence data analysis and accuracy of the predictions. During the first part of the presentation we will present the effect of chemical normalization on investigating correlations and building predictive models.
The second part of the talk will incorporate the results of model building on 163 ChEMBL targets extracted from the bioactivity benchmark set1. Results with different descriptor generation methods including ECFP fingerprints, MACCS key, structural properties, geometry properties and phy-chem properties will be discussed in detail. This part focuses on summarizing the results of more than 3000 Random Forest models.
Finally model development for ADMET targets will be highlighted including hERG cardiotoxicity prediction, permeability and blood brain barrier penetration. We will describe how these models can be built, analyzed, optimized and deployed using our new machine learning platform.
Efficient biomolecular structural data handling and analysis - Webinar with D...ChemAxon
In this joint event our experts are coming together to elaborate on the technical and scientific opportunities coming from this partnership. If you are working on the discovery of next generation drugs and using structure-based approach in your research, join us to learn how to leverage vast biomolecular structural data with innovative technologies.
Chemaxon is a software and services provider founded in 1998 with headquarters in Budapest and around 250 employees worldwide. Their software supports drug discovery workflows from target identification through clinical trials. They provide tools for biomolecule data management to help with challenges like understanding biological context across teams and preventing data silos. Their software allows users to model, register, standardize, visualize, and design complex biomolecules like peptides, oligonucleotides, conjugates, proteins and antibodies to facilitate collaboration in biotherapeutic fields.
Cheminfo Stories 2021 | Virtual UGM | Marvin Pro: The first releaseChemAxon
Marvin Pro is a new web-based chemical editor capable of drawing large synthesis schemes and biomolecules in publication quality. It can be extended with other modules and integrated with ChemAxon and third-party products. Some key features include impeccable visual quality matching journal styles, fast drawing using keyboard shortcuts, and chemical understanding for clean 2D structures and properties display. An alpha version is available on the Chemicalize website and the developers welcome feedback to help perfect the tool.
This document discusses enhanced stereochemistry representation in molecular structures, including absolute, and, and or labels. It explains that absolute labels indicate known exact stereochemistry, and labels indicate mixtures. Or labels signify a pure but unknown structure, while and labels represent mixtures where both configurations are present. Examples are given to illustrate how these labels can be used to define stereochemical mixtures and unknown structures. The document also demonstrates how chromatographic separation can be used to separate stereoisomer mixtures into pure components.
Intellectual property (IP) intelligence solutions designed for the way resear...ChemAxon
Leveraging IP intelligence through the researcher workflow requires the curation of chemistry patents including many thousands of molecules. This complex task is time-consuming and error-prone when done manually, whereas using ChemAxon’s ChemCuratora to analyze and extract chemical information in patents and other documents means the process can be done accurately in a fraction of the time.
GPS for Chemical Space - Digital Assistants to Support Molecule Design - Chem...ChemAxon
Boehringer Ingelheim's Nils Weskamp discusses eDesign: a computational platform for molecule design and optimization. This presentation explaing how to combine data, algorithms and user experience to impact compound design, and gives a glimpse into the agile and interdisciplinary teamwork as facilitated by Design Hub as a success factor for the development of digital tools.
Patent Data for Artificial Intelligence based Drug DiscoveryChemAxon
Han-Jo KIm from Standigm presents on using ChemAxon's ChemCurator in processing structures and relevant data from patents, from Google Patents, PDF and text format.
Cheminfo Stories APAC 2020 - Chemical Descriptors & Standardizers for Machine...ChemAxon
This document discusses chemical descriptors and standardizers that are useful for machine learning models. It introduces standardizers, which canonicalize chemical structures for comparability, and structure checkers, which detect errors. Extended connectivity fingerprints (ECFP) are described as circular fingerprints that encode molecular structure. Case studies demonstrate using ECFP descriptors and standardizers to train deep neural networks for hERG activity prediction, achieving over 80% accuracy. Combining ECFP with topological descriptors led to slightly better performance than ECFP alone in a random forest model. In summary, customizable fingerprints and standardizers allow application in different tasks, and combining fingerprints with other descriptors can increase model performance.
The Synergy platform is ChemAxon’s approach to SaaS solutions for chemistry related R&D data management. It provides an integrated system that cleans, organizes and links together pre-clinical research data and a collaborative workspace where people from multiple sites can work with each other, as well as with CROs and partners. Besides giving a summary of the fundamental platform components, the presentation guides the audience through the process of capturing chemical data in our Compound Registration tool, uploading and standardizing assay results and visualizing, as well as analyzing combined chemical data and biological results.
This webinar will guide you through the Design Hub platform for scientific design and discovery project management using an antiviral compound optimization example. The workflow starts from capturing the first observation and corresponding hypothesis, showcase compound design relying on a vast amount of information sources and predictive models, including the new hERG toxicity prediction and docking using RDock. It will highlight how tracking the fate of compound ideas created as draft virtual compounds through synthesis targets and finally registered samples is fluently managed by the interaction of Design Hub and Compound Registration system.
This document introduces ChemAxon's second generation JChem search engines, including the JChem PostgreSQL Cartridge and JChem Choral engine. It summarizes the key advantages like improved performance on large databases, enhanced tautomer matching, and new features. It also outlines how the different search products like cartridges and microservices are suited for different use cases and environments.
Cheminfo Stories APAC 2020 - Database management on desktop with JChem for Of...ChemAxon
This document provides an overview and summary of key features for JChem for Office and Instant JChem (IJC). JChem for Office allows embedding of live chemical structures in Microsoft Office files and includes features like chemical searching, properties calculations, and virtual library enumeration. IJC is a versatile data management framework that allows users to create, explore, share, and analyze chemical data through a project explorer interface, query builder, and grid/form views of data. It supports both structural and non-structural data management and analysis.
The document discusses Markush structures, which are used in patent claims to cover large numbers of similar chemical compounds using generalized structures. It presents tools for searching, visualizing, and extracting Markush structures from patents to help with tasks like idea validation, patent drafting, and understanding competitors' intellectual property. The case study demonstrates how these tools can be used to automatically validate that patent claims cover examples listed in the description.
JChem Microservices provide microservices in small separate modules for different areas of ChemAxon functionalities like chemical dataset searching, conversion between chemical file formats.
This document outlines the steps for migrating from the JChem Oracle Cartridge (JOC) to the JChem PostgreSQL Cartridge (JPC) or Choral. It discusses the reasons for migration, strategies for large ecosystems, non-cartridge migration steps, and cartridge-specific data and code migration steps. Key points include moving to new features, performance gains, compatibility with PostgreSQL and Amazon RDS, and references for more information.
ChemAxon's Compliance Checker - Cheminfo Stories 2020 Day 5ChemAxon
This document discusses Compliance Checker, a SaaS tool for compound screening and subscriptions. It offers different subscription tiers (Lite, Standard) with varying features - such as number of users, compounds screened per second, authentication method, and data storage. The Standard subscriptions include Basic, Medium, Professional and Premium options that provide different levels of support, performance, high availability, and license scope. The Lite subscription can be monthly, quarterly or annual based on the number of compounds that can be screened.
Chemicalize Pro - Cheminfo Stories 2020 Day 5ChemAxon
Chemicalize is an online SaaS product providing UI based chemical calculations, drawing and searching as well as API based endpoints for integrators and embeddable web components for website owners. In the presentation we introduce the service and showing the essence of the embeddable web components through a real-life use case focusing on the compliance questions.
Pasteur Institute User Story - Cheminfo Stories 2020 Day 5ChemAxon
Here, we present an updated version of iPPI-DB, our manually curated database of PPI modulators. In this release, the data model, the graphical interface and the tools to query the database have been completely redesigned. We used Chemaxon MarvinJS and JChem library to support this development. We added new PPI modulators, new PPI targets, and extended our focus to stabilizers of PPIs as well. Finally, we introduce a web application relying on crowdsourcing for the maintenance of the database. This application can be used outside of our group to collaboratively maintain iPPI-DB within a community of curators.
ChemAxon ChemLocator - Cheminfo Stories Day 5ChemAxon
ChemLocator is useful tool for extracting chemical and biological insights from documents. The count of yearly published articles, patents, journals etc. is wildly increasing. In this presentation we show how the tool will save you time and take some load off your shoulders when your job needs document searching. We show how to use it through its built-in web-based user interface and also introduce the way of API level integration into 3rd party applications.
An application of ChemAxon's platform for educationChemAxon
Online tools for chemical education are widely used in the last decade. Several state of the art homework and test systems are available for chemistry online learning. Most of these applications are based on chemistry textbooks and uses well-curated questions created by professionals to help students to master a certain division of chemistry.
Our ultimate goal is to support online learning and help students practice and master chemistry and biochemistry. ChemAxon’s learning platform has a friendly and intuitive interface to easily create and share online learning materials. Tools like Marvin JS, BioEddie and JChemBase are used to automatically evaluate and grade student’s assignments.
ChemAxon provides an open cloud-based learning hub to enhance classroom collaboration and increase the effectiveness of learning. This online learning platform is a powerful tool to help teachers in coaching students based on progress tracking.
Chemical intelligence that makes hidden knowledge effortlessly reachableChemAxon
The knowledge, that is being produced and stored in the forms of reports, patents and scientific journal articles is expanding exponentially. Although, the unstructured nature of such contents impose constraints for seamless information access and scientific decision support. Chemistry is a unique field in this regard, for two reasons. First, the nomenclature is verbose in a sense that a chemical structure can be represented with various synonyms, for example traditional name, IUPAC name or a wide range of brand names or chemical formats (SMILES). Second, the navigation in the knowledge base, with queries related to the encapsulated chemical space, calls for peculiar search methods like similarity-based or substructure searches.
Our study highlights computational approaches to turn chemistry related knowledge stored in all the open access articles easily accessible. We present our results obtained on this large corpus through the following workflow: i) large-scale conversion of text content to chemical objects, ii) automated preparation of databases to store and organize relevant data, and iii) analysis of the collected chemistry space.
Extraction of chemical objects was done from nearly 1.9M articles that stretches the chemical space of open access scientific literature with ChemLocator application. Chemical space was analysed with calculation of fingerprint-based chemical similarity matrix and clustering by MadFast Similarity Search. In order to explore the scaffold diversity of this exclusive chemical space, the obtained set was fragmented to yield rings and ring systems. Hidden relationships were explored by combining text and chemical information in graph data model and related visualization.
In summary, our use-case highlights the potential of novel technologies to pre-process, search and explore the information network enfolded in large document sets on the field of chemistry.
Deep analysis of chemical patents and Markush claimsChemAxon
This document discusses the importance of Markush structures in patents and describes a technology for analyzing Markush claims in chemical patents. It notes that around 12% of US patents contain Markush claims covering thousands of structures. Existing Markush databases and services have limitations. The described Markush technology can represent complex Markush structures, search patent databases, visualize hits and non-hits, and assist with drafting new Markush claims. An example workflow uses the technology to extract Markush claims from relevant patents, validate structures against a project's ideas, and integrate the information into an in-house database. The technology aims to help write better patents and integrate IP knowledge into early-stage discovery.
Bridging the gap between small molecule and biologics editingChemAxon
An increasing number of new FDA approved drugs are biologics; in 2015 alone, 19 out of the 51 approved drugs were biological entities. Increasingly, the development of these complex drugs requires chemists and biologists to collaborate closely from ideation to product maturity. During this process candidate molecules undergo iterative changes which need to be communicated precisely and unambiguously to all researchers involved in the project. Although the cheminformatics world is well covered in terms of software to draw, store, search, report and manage small molecules, there is currently no efficient way to handle biological entities in the same manner.
ChemAxon, a well-known cheminformatics software provider, recognized and bridged this information gap between biology and chemistry by the development and integration of Biomolecule Toolkit and the biological editor, BioEddie. We provide unambiguous representation for biologics: peptides, oligonucleotides, proteins, antibodies, antibody drug conjugates etc., including those containing unnatural and chemically-modified components with the ability to define ambiguous structural elements. The standardized representation, paired with the ability to round-trip between standard chemical and biological file formats (MDL MOL to HELM conversion and vice versa), allows researchers to keep a single data store of molecular assets (Biomolecule Toolkit), in which they can query based on sequences, chemical structure or metadata. Relevant molecules can be exported for further processing in other computational tools. In this poster, we will demonstrate the novelty of our approach and present a couple of case studies: one for CHEMBL v21 peptides dataset and one for antibody registration.
EUGM15 - Zoltán Simon (Printnet): Drug Profile Matching - Drug Discovery by P...ChemAxon
Most drugs exert their effects via multi-target interactions, as hypothesized by polypharmacology. Here we introduce Drug Profile Matching (DPM) which is able to relate complex drug-protein interaction profiles with effect and target profiles. Structural data and registered effect profiles of all small-molecule drugs were collected and interactions to a series of non-target protein binding sites of each drug were calculated. Statistical analyses confirmed close relationships between the studied 177 effect and 77 target categories and the in silico generated interaction profiles of cca. 1,200 FDA-approved small-molecule drugs. Receiver Operating Characteristic analysis and 10-fold cross-validation was performed to assess the accuracy and robustness of the method. Based on the found relationships, the effect and target profiles of drugs can be revealed in their entirety, and hitherto uncovered effects and targets can be predicted in a systematic manner.
In order to investigate the predictive power of DPM, four effect categories (PPAR agonist, angiotensin-converting enzyme inhibitor, cyclooxygenase inhibitor and dopamine agent) were selected and predictions in the set of the FDA-approved small-molecule drugs were verified by literature analysis and experimental tests.
Moreover, a large set consisting of 600,000 druglike molecules was selected from a database of 50 million compounds and their interaction profiles were generated. Based on these profiles and chemical similarity considerations, predictions were calculated and tested experimentally to find new candidates that are chemically dissimilar to the reference drugs.
Odoo releases a new update every year. The latest version, Odoo 17, came out in October 2023. It brought many improvements to the user interface and user experience, along with new features in modules like accounting, marketing, manufacturing, websites, and more.
The Odoo 17 update has been a hot topic among startups, mid-sized businesses, large enterprises, and Odoo developers aiming to grow their businesses. Since it is now already the first quarter of 2024, you must have a clear idea of what Odoo 17 entails and what it can offer your business if you are still not aware of it.
This blog covers the features and functionalities. Explore the entire blog and get in touch with expert Odoo ERP consultants to leverage Odoo 17 and its features for your business too.
An Overview of Odoo ERP
Odoo ERP was first released as OpenERP software in February 2005. It is a suite of business applications used for ERP, CRM, eCommerce, websites, and project management. Ten years ago, the Odoo Enterprise edition was launched to help fund the Odoo Community version.
When you compare Odoo Community and Enterprise, the Enterprise edition offers exclusive features like mobile app access, Odoo Studio customisation, Odoo hosting, and unlimited functional support.
Today, Odoo is a well-known name used by companies of all sizes across various industries, including manufacturing, retail, accounting, marketing, healthcare, IT consulting, and R&D.
The latest version, Odoo 17, has been available since October 2023. Key highlights of this update include:
Enhanced user experience with improvements to the command bar, faster backend page loading, and multiple dashboard views.
Instant report generation, credit limit alerts for sales and invoices, separate OCR settings for invoice creation, and an auto-complete feature for forms in the accounting module.
Improved image handling and global attribute changes for mailing lists in email marketing.
A default auto-signature option and a refuse-to-sign option in HR modules.
Options to divide and merge manufacturing orders, track the status of manufacturing orders, and more in the MRP module.
Dark mode in Odoo 17.
Now that the Odoo 17 announcement is official, let’s look at what’s new in Odoo 17!
What is Odoo ERP 17?
Odoo 17 is the latest version of one of the world’s leading open-source enterprise ERPs. This version has come up with significant improvements explained here in this blog. Also, this new version aims to introduce features that enhance time-saving, efficiency, and productivity for users across various organisations.
Odoo 17, released at the Odoo Experience 2023, brought notable improvements to the user interface and added new functionalities with enhancements in performance, accessibility, data analysis, and management, further expanding its reach in the market.
GPS for Chemical Space - Digital Assistants to Support Molecule Design - Chem...ChemAxon
Boehringer Ingelheim's Nils Weskamp discusses eDesign: a computational platform for molecule design and optimization. This presentation explaing how to combine data, algorithms and user experience to impact compound design, and gives a glimpse into the agile and interdisciplinary teamwork as facilitated by Design Hub as a success factor for the development of digital tools.
Patent Data for Artificial Intelligence based Drug DiscoveryChemAxon
Han-Jo KIm from Standigm presents on using ChemAxon's ChemCurator in processing structures and relevant data from patents, from Google Patents, PDF and text format.
Cheminfo Stories APAC 2020 - Chemical Descriptors & Standardizers for Machine...ChemAxon
This document discusses chemical descriptors and standardizers that are useful for machine learning models. It introduces standardizers, which canonicalize chemical structures for comparability, and structure checkers, which detect errors. Extended connectivity fingerprints (ECFP) are described as circular fingerprints that encode molecular structure. Case studies demonstrate using ECFP descriptors and standardizers to train deep neural networks for hERG activity prediction, achieving over 80% accuracy. Combining ECFP with topological descriptors led to slightly better performance than ECFP alone in a random forest model. In summary, customizable fingerprints and standardizers allow application in different tasks, and combining fingerprints with other descriptors can increase model performance.
The Synergy platform is ChemAxon’s approach to SaaS solutions for chemistry related R&D data management. It provides an integrated system that cleans, organizes and links together pre-clinical research data and a collaborative workspace where people from multiple sites can work with each other, as well as with CROs and partners. Besides giving a summary of the fundamental platform components, the presentation guides the audience through the process of capturing chemical data in our Compound Registration tool, uploading and standardizing assay results and visualizing, as well as analyzing combined chemical data and biological results.
This webinar will guide you through the Design Hub platform for scientific design and discovery project management using an antiviral compound optimization example. The workflow starts from capturing the first observation and corresponding hypothesis, showcase compound design relying on a vast amount of information sources and predictive models, including the new hERG toxicity prediction and docking using RDock. It will highlight how tracking the fate of compound ideas created as draft virtual compounds through synthesis targets and finally registered samples is fluently managed by the interaction of Design Hub and Compound Registration system.
This document introduces ChemAxon's second generation JChem search engines, including the JChem PostgreSQL Cartridge and JChem Choral engine. It summarizes the key advantages like improved performance on large databases, enhanced tautomer matching, and new features. It also outlines how the different search products like cartridges and microservices are suited for different use cases and environments.
Cheminfo Stories APAC 2020 - Database management on desktop with JChem for Of...ChemAxon
This document provides an overview and summary of key features for JChem for Office and Instant JChem (IJC). JChem for Office allows embedding of live chemical structures in Microsoft Office files and includes features like chemical searching, properties calculations, and virtual library enumeration. IJC is a versatile data management framework that allows users to create, explore, share, and analyze chemical data through a project explorer interface, query builder, and grid/form views of data. It supports both structural and non-structural data management and analysis.
The document discusses Markush structures, which are used in patent claims to cover large numbers of similar chemical compounds using generalized structures. It presents tools for searching, visualizing, and extracting Markush structures from patents to help with tasks like idea validation, patent drafting, and understanding competitors' intellectual property. The case study demonstrates how these tools can be used to automatically validate that patent claims cover examples listed in the description.
JChem Microservices provide microservices in small separate modules for different areas of ChemAxon functionalities like chemical dataset searching, conversion between chemical file formats.
This document outlines the steps for migrating from the JChem Oracle Cartridge (JOC) to the JChem PostgreSQL Cartridge (JPC) or Choral. It discusses the reasons for migration, strategies for large ecosystems, non-cartridge migration steps, and cartridge-specific data and code migration steps. Key points include moving to new features, performance gains, compatibility with PostgreSQL and Amazon RDS, and references for more information.
ChemAxon's Compliance Checker - Cheminfo Stories 2020 Day 5ChemAxon
This document discusses Compliance Checker, a SaaS tool for compound screening and subscriptions. It offers different subscription tiers (Lite, Standard) with varying features - such as number of users, compounds screened per second, authentication method, and data storage. The Standard subscriptions include Basic, Medium, Professional and Premium options that provide different levels of support, performance, high availability, and license scope. The Lite subscription can be monthly, quarterly or annual based on the number of compounds that can be screened.
Chemicalize Pro - Cheminfo Stories 2020 Day 5ChemAxon
Chemicalize is an online SaaS product providing UI based chemical calculations, drawing and searching as well as API based endpoints for integrators and embeddable web components for website owners. In the presentation we introduce the service and showing the essence of the embeddable web components through a real-life use case focusing on the compliance questions.
Pasteur Institute User Story - Cheminfo Stories 2020 Day 5ChemAxon
Here, we present an updated version of iPPI-DB, our manually curated database of PPI modulators. In this release, the data model, the graphical interface and the tools to query the database have been completely redesigned. We used Chemaxon MarvinJS and JChem library to support this development. We added new PPI modulators, new PPI targets, and extended our focus to stabilizers of PPIs as well. Finally, we introduce a web application relying on crowdsourcing for the maintenance of the database. This application can be used outside of our group to collaboratively maintain iPPI-DB within a community of curators.
ChemAxon ChemLocator - Cheminfo Stories Day 5ChemAxon
ChemLocator is useful tool for extracting chemical and biological insights from documents. The count of yearly published articles, patents, journals etc. is wildly increasing. In this presentation we show how the tool will save you time and take some load off your shoulders when your job needs document searching. We show how to use it through its built-in web-based user interface and also introduce the way of API level integration into 3rd party applications.
An application of ChemAxon's platform for educationChemAxon
Online tools for chemical education are widely used in the last decade. Several state of the art homework and test systems are available for chemistry online learning. Most of these applications are based on chemistry textbooks and uses well-curated questions created by professionals to help students to master a certain division of chemistry.
Our ultimate goal is to support online learning and help students practice and master chemistry and biochemistry. ChemAxon’s learning platform has a friendly and intuitive interface to easily create and share online learning materials. Tools like Marvin JS, BioEddie and JChemBase are used to automatically evaluate and grade student’s assignments.
ChemAxon provides an open cloud-based learning hub to enhance classroom collaboration and increase the effectiveness of learning. This online learning platform is a powerful tool to help teachers in coaching students based on progress tracking.
Chemical intelligence that makes hidden knowledge effortlessly reachableChemAxon
The knowledge, that is being produced and stored in the forms of reports, patents and scientific journal articles is expanding exponentially. Although, the unstructured nature of such contents impose constraints for seamless information access and scientific decision support. Chemistry is a unique field in this regard, for two reasons. First, the nomenclature is verbose in a sense that a chemical structure can be represented with various synonyms, for example traditional name, IUPAC name or a wide range of brand names or chemical formats (SMILES). Second, the navigation in the knowledge base, with queries related to the encapsulated chemical space, calls for peculiar search methods like similarity-based or substructure searches.
Our study highlights computational approaches to turn chemistry related knowledge stored in all the open access articles easily accessible. We present our results obtained on this large corpus through the following workflow: i) large-scale conversion of text content to chemical objects, ii) automated preparation of databases to store and organize relevant data, and iii) analysis of the collected chemistry space.
Extraction of chemical objects was done from nearly 1.9M articles that stretches the chemical space of open access scientific literature with ChemLocator application. Chemical space was analysed with calculation of fingerprint-based chemical similarity matrix and clustering by MadFast Similarity Search. In order to explore the scaffold diversity of this exclusive chemical space, the obtained set was fragmented to yield rings and ring systems. Hidden relationships were explored by combining text and chemical information in graph data model and related visualization.
In summary, our use-case highlights the potential of novel technologies to pre-process, search and explore the information network enfolded in large document sets on the field of chemistry.
Deep analysis of chemical patents and Markush claimsChemAxon
This document discusses the importance of Markush structures in patents and describes a technology for analyzing Markush claims in chemical patents. It notes that around 12% of US patents contain Markush claims covering thousands of structures. Existing Markush databases and services have limitations. The described Markush technology can represent complex Markush structures, search patent databases, visualize hits and non-hits, and assist with drafting new Markush claims. An example workflow uses the technology to extract Markush claims from relevant patents, validate structures against a project's ideas, and integrate the information into an in-house database. The technology aims to help write better patents and integrate IP knowledge into early-stage discovery.
Bridging the gap between small molecule and biologics editingChemAxon
An increasing number of new FDA approved drugs are biologics; in 2015 alone, 19 out of the 51 approved drugs were biological entities. Increasingly, the development of these complex drugs requires chemists and biologists to collaborate closely from ideation to product maturity. During this process candidate molecules undergo iterative changes which need to be communicated precisely and unambiguously to all researchers involved in the project. Although the cheminformatics world is well covered in terms of software to draw, store, search, report and manage small molecules, there is currently no efficient way to handle biological entities in the same manner.
ChemAxon, a well-known cheminformatics software provider, recognized and bridged this information gap between biology and chemistry by the development and integration of Biomolecule Toolkit and the biological editor, BioEddie. We provide unambiguous representation for biologics: peptides, oligonucleotides, proteins, antibodies, antibody drug conjugates etc., including those containing unnatural and chemically-modified components with the ability to define ambiguous structural elements. The standardized representation, paired with the ability to round-trip between standard chemical and biological file formats (MDL MOL to HELM conversion and vice versa), allows researchers to keep a single data store of molecular assets (Biomolecule Toolkit), in which they can query based on sequences, chemical structure or metadata. Relevant molecules can be exported for further processing in other computational tools. In this poster, we will demonstrate the novelty of our approach and present a couple of case studies: one for CHEMBL v21 peptides dataset and one for antibody registration.
EUGM15 - Zoltán Simon (Printnet): Drug Profile Matching - Drug Discovery by P...ChemAxon
Most drugs exert their effects via multi-target interactions, as hypothesized by polypharmacology. Here we introduce Drug Profile Matching (DPM) which is able to relate complex drug-protein interaction profiles with effect and target profiles. Structural data and registered effect profiles of all small-molecule drugs were collected and interactions to a series of non-target protein binding sites of each drug were calculated. Statistical analyses confirmed close relationships between the studied 177 effect and 77 target categories and the in silico generated interaction profiles of cca. 1,200 FDA-approved small-molecule drugs. Receiver Operating Characteristic analysis and 10-fold cross-validation was performed to assess the accuracy and robustness of the method. Based on the found relationships, the effect and target profiles of drugs can be revealed in their entirety, and hitherto uncovered effects and targets can be predicted in a systematic manner.
In order to investigate the predictive power of DPM, four effect categories (PPAR agonist, angiotensin-converting enzyme inhibitor, cyclooxygenase inhibitor and dopamine agent) were selected and predictions in the set of the FDA-approved small-molecule drugs were verified by literature analysis and experimental tests.
Moreover, a large set consisting of 600,000 druglike molecules was selected from a database of 50 million compounds and their interaction profiles were generated. Based on these profiles and chemical similarity considerations, predictions were calculated and tested experimentally to find new candidates that are chemically dissimilar to the reference drugs.
Odoo releases a new update every year. The latest version, Odoo 17, came out in October 2023. It brought many improvements to the user interface and user experience, along with new features in modules like accounting, marketing, manufacturing, websites, and more.
The Odoo 17 update has been a hot topic among startups, mid-sized businesses, large enterprises, and Odoo developers aiming to grow their businesses. Since it is now already the first quarter of 2024, you must have a clear idea of what Odoo 17 entails and what it can offer your business if you are still not aware of it.
This blog covers the features and functionalities. Explore the entire blog and get in touch with expert Odoo ERP consultants to leverage Odoo 17 and its features for your business too.
An Overview of Odoo ERP
Odoo ERP was first released as OpenERP software in February 2005. It is a suite of business applications used for ERP, CRM, eCommerce, websites, and project management. Ten years ago, the Odoo Enterprise edition was launched to help fund the Odoo Community version.
When you compare Odoo Community and Enterprise, the Enterprise edition offers exclusive features like mobile app access, Odoo Studio customisation, Odoo hosting, and unlimited functional support.
Today, Odoo is a well-known name used by companies of all sizes across various industries, including manufacturing, retail, accounting, marketing, healthcare, IT consulting, and R&D.
The latest version, Odoo 17, has been available since October 2023. Key highlights of this update include:
Enhanced user experience with improvements to the command bar, faster backend page loading, and multiple dashboard views.
Instant report generation, credit limit alerts for sales and invoices, separate OCR settings for invoice creation, and an auto-complete feature for forms in the accounting module.
Improved image handling and global attribute changes for mailing lists in email marketing.
A default auto-signature option and a refuse-to-sign option in HR modules.
Options to divide and merge manufacturing orders, track the status of manufacturing orders, and more in the MRP module.
Dark mode in Odoo 17.
Now that the Odoo 17 announcement is official, let’s look at what’s new in Odoo 17!
What is Odoo ERP 17?
Odoo 17 is the latest version of one of the world’s leading open-source enterprise ERPs. This version has come up with significant improvements explained here in this blog. Also, this new version aims to introduce features that enhance time-saving, efficiency, and productivity for users across various organisations.
Odoo 17, released at the Odoo Experience 2023, brought notable improvements to the user interface and added new functionalities with enhancements in performance, accessibility, data analysis, and management, further expanding its reach in the market.
Mobile App Development Company In Noida | Drona InfotechDrona Infotech
React.js, a JavaScript library developed by Facebook, has gained immense popularity for building user interfaces, especially for single-page applications. Over the years, React has evolved and expanded its capabilities, becoming a preferred choice for mobile app development. This article will explore why React.js is an excellent choice for the Best Mobile App development company in Noida.
Visit Us For Information: https://www.linkedin.com/pulse/what-makes-reactjs-stand-out-mobile-app-development-rajesh-rai-pihvf/
Unlock the Secrets to Effortless Video Creation with Invideo: Your Ultimate G...The Third Creative Media
"Navigating Invideo: A Comprehensive Guide" is an essential resource for anyone looking to master Invideo, an AI-powered video creation tool. This guide provides step-by-step instructions, helpful tips, and comparisons with other AI video creators. Whether you're a beginner or an experienced video editor, you'll find valuable insights to enhance your video projects and bring your creative ideas to life.
Nashik's top web development company, Upturn India Technologies, crafts innovative digital solutions for your success. Partner with us and achieve your goals
Manyata Tech Park Bangalore_ Infrastructure, Facilities and Morenarinav14
Located in the bustling city of Bangalore, Manyata Tech Park stands as one of India’s largest and most prominent tech parks, playing a pivotal role in shaping the city’s reputation as the Silicon Valley of India. Established to cater to the burgeoning IT and technology sectors
Liberarsi dai framework con i Web Component.pptxMassimo Artizzu
In Italian
Presentazione sulle feature e l'utilizzo dei Web Component nell sviluppo di pagine e applicazioni web. Racconto delle ragioni storiche dell'avvento dei Web Component. Evidenziazione dei vantaggi e delle sfide poste, indicazione delle best practices, con particolare accento sulla possibilità di usare web component per facilitare la migrazione delle proprie applicazioni verso nuovi stack tecnologici.
Everything You Need to Know About X-Sign: The eSign Functionality of XfilesPr...XfilesPro
Wondering how X-Sign gained popularity in a quick time span? This eSign functionality of XfilesPro DocuPrime has many advancements to offer for Salesforce users. Explore them now!
Orca: Nocode Graphical Editor for Container OrchestrationPedro J. Molina
Tool demo on CEDI/SISTEDES/JISBD2024 at A Coruña, Spain. 2024.06.18
"Orca: Nocode Graphical Editor for Container Orchestration"
by Pedro J. Molina PhD. from Metadev
8 Best Automated Android App Testing Tool and Framework in 2024.pdfkalichargn70th171
Regarding mobile operating systems, two major players dominate our thoughts: Android and iPhone. With Android leading the market, software development companies are focused on delivering apps compatible with this OS. Ensuring an app's functionality across various Android devices, OS versions, and hardware specifications is critical, making Android app testing essential.
Superpower Your Apache Kafka Applications Development with Complementary Open...Paul Brebner
Kafka Summit talk (Bangalore, India, May 2, 2024, https://events.bizzabo.com/573863/agenda/session/1300469 )
Many Apache Kafka use cases take advantage of Kafka’s ability to integrate multiple heterogeneous systems for stream processing and real-time machine learning scenarios. But Kafka also exists in a rich ecosystem of related but complementary stream processing technologies and tools, particularly from the open-source community. In this talk, we’ll take you on a tour of a selection of complementary tools that can make Kafka even more powerful. We’ll focus on tools for stream processing and querying, streaming machine learning, stream visibility and observation, stream meta-data, stream visualisation, stream development including testing and the use of Generative AI and LLMs, and stream performance and scalability. By the end you will have a good idea of the types of Kafka “superhero” tools that exist, which are my favourites (and what superpowers they have), and how they combine to save your Kafka applications development universe from swamploads of data stagnation monsters!
🏎️Tech Transformation: DevOps Insights from the Experts 👩💻campbellclarkson
Connect with fellow Trailblazers, learn from industry experts Glenda Thomson (Salesforce, Principal Technical Architect) and Will Dinn (Judo Bank, Salesforce Development Lead), and discover how to harness DevOps tools with Salesforce.
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdfBaha Majid
IBM watsonx Code Assistant for Z, our latest Generative AI-assisted mainframe application modernization solution. Mainframe (IBM Z) application modernization is a topic that every mainframe client is addressing to various degrees today, driven largely from digital transformation. With generative AI comes the opportunity to reimagine the mainframe application modernization experience. Infusing generative AI will enable speed and trust, help de-risk, and lower total costs associated with heavy-lifting application modernization initiatives. This document provides an overview of the IBM watsonx Code Assistant for Z which uses the power of generative AI to make it easier for developers to selectively modernize COBOL business services while maintaining mainframe qualities of service.