Evaluating the Quality and Performance of Automatic Atom Mapping AlgorithmsNextMove Software
The document evaluates and compares the performance of five automatic atom mapping algorithms: Pipeline Pilot, Marvin, Indigo, ICMAP, and ChemDraw. It finds that ICMAP produced the best quality mappings, correctly mapping all product atoms. However, all the algorithms showed room for improvement, such as in handling more complex mappings with reactant reuse or single atom mappings. The document concludes atom mapping is more complex than maximal common subgraph matching and presents results on various algorithms' performance using several benchmark reaction datasets.
CINF 13: Pistachio - Search and Faceting of Large Reaction DatabasesNextMove Software
We have previously described the extraction of reactions from US and European patents. This talk will discuss the assembly of over six million extracted reaction details consisting of the connection tables, procedure, quantities, solvents, catalysts and yields into a searchable "read-only" Electronic Lab Notebook.
In addition to reactions details, concepts including diseases, drug targets, and assignees are recognised from the patent documents and normalised to appropriate ontologies. Each normalised term is paired with the reaction details found in the document to allow intuitive cross concept querying (e.g. "GlaxoSmithKline C-C Bond Formation greater than 80% yield Myocardial Infarction"). Reactions are classified and assigned to leafs in the RXNO Ontology. The ontologies are used to provide organisation, faceting, and filtering of results. The reaction classification also provides a precise atom mapping that facilitates structural transformation queries and can improve reaction diagram layout.
Through improvements in substructure search technology we will demonstrate several types of chemical synthesis queries that can be efficiently answered. The combination of high performance chemical searching and additional document terms provides a powerful exploratory and trend analysis tool for chemists.
Pharmaceutical industry best practices in lessons learned: ELN implementation...NextMove Software
This document summarizes an implementation of Merck's reaction review policy in another pharmaceutical company's electronic laboratory notebook (ELN). Key points include:
- The policy was implemented to reduce laboratory accidents by learning from past incidents.
- It involved adding new fields to the ELN like "reaction vessel size" to capture scale-dependent hazards.
- Algorithms were developed to categorize compounds by hazards and flag risky experiments based on criteria like reactive functional groups, physical properties, and reaction types.
- Future work aims to more accurately represent mixtures, predict compound properties, and integrate the system with other chemistry databases and ontologies.
E:\Class Iii Nr 418 Dynamics Of Teams1209psharpnack
Groups and teams are collections of people working toward a common goal. Groups are generally broader while teams have more defined roles and objectives. Effective teams require contributions from all members, shared goals and accountability, and a variety of skills and personalities. Teams progress through forming, storming, norming, performing, and adjourning stages. Leaders can adopt different styles like autocratic, consultative, delegative, or consensus-based approaches. Building effective teams relies on factors such as clear communication, addressing issues directly, valuing all members, and recognizing accomplishments.
This document summarizes advances in automatic chemical spelling correction. It discusses using edit distances and dynamic programming to correct spelling errors. Examples are given of correcting errors in chemical names, CAS registry numbers, and protein target names. Benchmarking on patent data shows automatic correction improves recall of chemical entity recognition by around 20-40%. The techniques allow fuzzy matching of chemical structures and nomenclature rules.
Efficient Searching and Similarity of Unmapped Reactions: Application to ELN ...NextMove Software
The document discusses challenges in analyzing reaction data from electronic laboratory notebooks (ELNs) to better understand chemical reactions. It outlines approaches to standardize reaction representation, define reaction identity, improve reaction depiction and searching, calculate reaction similarity, and classify reactions. The goal is to enable medicinal chemists to make more effective use of reaction data in ELNs to improve drug discovery processes.
SmallWorld : Efficient Maximum Common Subgraph Searching of Large Chemical Da...NextMove Software
The document describes a new method called SmallWorld for efficiently searching large chemical databases to find maximum common subgraphs. SmallWorld indexes all possible subgraphs of molecules in a database, allowing it to quickly find structural similarities between a query molecule and database molecules. It was shown to outperform fingerprint-based methods on large datasets due to sub-linear scaling. The method may become the standard approach for chemical similarity calculations as computers continue to increase in power.
Evaluating the Quality and Performance of Automatic Atom Mapping AlgorithmsNextMove Software
The document evaluates and compares the performance of five automatic atom mapping algorithms: Pipeline Pilot, Marvin, Indigo, ICMAP, and ChemDraw. It finds that ICMAP produced the best quality mappings, correctly mapping all product atoms. However, all the algorithms showed room for improvement, such as in handling more complex mappings with reactant reuse or single atom mappings. The document concludes atom mapping is more complex than maximal common subgraph matching and presents results on various algorithms' performance using several benchmark reaction datasets.
CINF 13: Pistachio - Search and Faceting of Large Reaction DatabasesNextMove Software
We have previously described the extraction of reactions from US and European patents. This talk will discuss the assembly of over six million extracted reaction details consisting of the connection tables, procedure, quantities, solvents, catalysts and yields into a searchable "read-only" Electronic Lab Notebook.
In addition to reactions details, concepts including diseases, drug targets, and assignees are recognised from the patent documents and normalised to appropriate ontologies. Each normalised term is paired with the reaction details found in the document to allow intuitive cross concept querying (e.g. "GlaxoSmithKline C-C Bond Formation greater than 80% yield Myocardial Infarction"). Reactions are classified and assigned to leafs in the RXNO Ontology. The ontologies are used to provide organisation, faceting, and filtering of results. The reaction classification also provides a precise atom mapping that facilitates structural transformation queries and can improve reaction diagram layout.
Through improvements in substructure search technology we will demonstrate several types of chemical synthesis queries that can be efficiently answered. The combination of high performance chemical searching and additional document terms provides a powerful exploratory and trend analysis tool for chemists.
Pharmaceutical industry best practices in lessons learned: ELN implementation...NextMove Software
This document summarizes an implementation of Merck's reaction review policy in another pharmaceutical company's electronic laboratory notebook (ELN). Key points include:
- The policy was implemented to reduce laboratory accidents by learning from past incidents.
- It involved adding new fields to the ELN like "reaction vessel size" to capture scale-dependent hazards.
- Algorithms were developed to categorize compounds by hazards and flag risky experiments based on criteria like reactive functional groups, physical properties, and reaction types.
- Future work aims to more accurately represent mixtures, predict compound properties, and integrate the system with other chemistry databases and ontologies.
E:\Class Iii Nr 418 Dynamics Of Teams1209psharpnack
Groups and teams are collections of people working toward a common goal. Groups are generally broader while teams have more defined roles and objectives. Effective teams require contributions from all members, shared goals and accountability, and a variety of skills and personalities. Teams progress through forming, storming, norming, performing, and adjourning stages. Leaders can adopt different styles like autocratic, consultative, delegative, or consensus-based approaches. Building effective teams relies on factors such as clear communication, addressing issues directly, valuing all members, and recognizing accomplishments.
This document summarizes advances in automatic chemical spelling correction. It discusses using edit distances and dynamic programming to correct spelling errors. Examples are given of correcting errors in chemical names, CAS registry numbers, and protein target names. Benchmarking on patent data shows automatic correction improves recall of chemical entity recognition by around 20-40%. The techniques allow fuzzy matching of chemical structures and nomenclature rules.
Efficient Searching and Similarity of Unmapped Reactions: Application to ELN ...NextMove Software
The document discusses challenges in analyzing reaction data from electronic laboratory notebooks (ELNs) to better understand chemical reactions. It outlines approaches to standardize reaction representation, define reaction identity, improve reaction depiction and searching, calculate reaction similarity, and classify reactions. The goal is to enable medicinal chemists to make more effective use of reaction data in ELNs to improve drug discovery processes.
SmallWorld : Efficient Maximum Common Subgraph Searching of Large Chemical Da...NextMove Software
The document describes a new method called SmallWorld for efficiently searching large chemical databases to find maximum common subgraphs. SmallWorld indexes all possible subgraphs of molecules in a database, allowing it to quickly find structural similarities between a query molecule and database molecules. It was shown to outperform fingerprint-based methods on large datasets due to sub-linear scaling. The method may become the standard approach for chemical similarity calculations as computers continue to increase in power.
mcule.com is a public web service for drug discovery based in Budapest, Hungary. It provides an up-to-date compound database that can be searched simply or with complex queries, integrated workflows for virtual screening, and the ability to order compounds from multiple suppliers in a single package. The service aims to offer unlimited computational capacity through cloud computing.
Chemical Text Mining for Current Awareness of Pharmaceutical PatentsNextMove Software
This document summarizes a presentation given at the ACS National Meeting in Philadelphia on August 19th, 2012 about chemical text mining of pharmaceutical patents. The presentation discussed trends in US patent applications for pharmaceuticals from 2002-2012, workflows for extracting and analyzing information from patent texts, and tools like LeadMine and PatFetch that can recognize chemical entities and access patent texts programmatically.
Recent improvements in marvin v6 reaction atom mapping and its application to...NextMove Software
Automatic atom mapping attempts to determine the correspondence between the atoms of the reactants and products of a chemical reaction. Such mappings are useful for allowing greater specificity in queries of reaction databases. Recently there has been increased interest in their use to assist in the validation and standardisation of reactions in pharmaceutical ELNs (electronic lab notebooks). Atom mappings can, for example, detect if a reactant is missing or if a reactant does not contribute atoms to the product and hence may be better stored as an agent.
We have evaluated the performance of the new atom mapping algorithm introduced with Marvin v6 compared to the prior version on a publically available dataset extracted from the patent literature and on reactions from multiple pharmaceutical ELNs. Dramatic improvements are observed in all cases both in the percentage of reactions that can be successfully atom-mapped and the quality of mappings produced.
Finally we examine the difficulties that remain in validating reactions for which a complete atom mapping is not possible, such as for “routine” reactions where the reactant that was added is missing.
The document summarizes a presentation about green chemistry and engineering given by Ken Rollins to the American Institute of Chemical Engineers – Delaware Valley Section. It discusses the 12 principles of green chemistry, which focus on preventing waste, using safer and renewable materials, and designing for reduced environmental impact. It also outlines the 12 principles of green engineering, including ensuring inherent safety. The presentation provides examples of applying these principles, such as using catalytic reactions instead of excess reagents, and assessing solvents based on their safety and environmental impact ratings.
Yale University has transformed its former pharmaceutical campus into a research hub known as Yale West Campus. The 136-acre campus contains over 1.6 million square feet of research labs, administrative offices, and specialty storage facilities. Yale aims to establish interdisciplinary institutes that bring together faculty from across the university to work on challenges in health, environment and energy. The director of research technology discusses challenges in integrating the new campus, developing its identity and vision, and planning state-of-the-art research facilities. Several case studies highlight how old buildings have been repurposed and new centers designed to foster collaboration among researchers.
Integrating Analyzers with Automation Systems: Oil and Gas by David SchihabelISA Interchange
The document discusses how gas analyzers are integrated with automation systems for real-time control of oil and gas operations. It describes a system that currently produces 40,000 bbls of oil, 20,000 bbls of natural gas liquids, and 230 million standard cubic feet per day of natural gas. The quality of gas streams is maintained through real-time analysis of the permeate gas stream, as off-spec gas could shut down the entire production system. It also details a gas treating unit that removes CO2 from residue gas streams using analyzer results to control inlet and outlet blending valves for the single operating column.
The document discusses green chemistry and engineering principles presented by Ken Rollins at the American Institute of Chemical Engineers. It outlines the 12 principles of green chemistry which focus on preventing waste, safer chemicals and syntheses, renewable resources, energy efficiency and more. It also discusses the 12 principles of green engineering, such as ensuring inherent safety, preventing waste, maximizing efficiencies and integrating material and energy flows. The talk provided an overview of green chemistry and engineering concepts aimed at minimizing environmental impact.
Virtual Reaction Service Using Chem Axon Reactor July06DanielSButler
The document discusses implementing chemical reactions virtually using a software called Reactor. It provides examples of developing aromatic, heterocyclic, and amide reactions virtually and applying charge and pKa plugins. It also discusses considerations for accurately translating real reactions to the virtual world, including regioselectivity, stereochemistry, and resolving molecules to comprehensively cover chemical space.
Efficient Perception of Proteins and Nucleic Acids from Atomic ConnectivityNextMove Software
This document summarizes a presentation about efficiently perceiving and depicting proteins and nucleic acids from atomic connectivity data. It discusses challenges in bridging cheminformatics and bioinformatics for peptides. The presentation describes algorithms for recognizing biomolecule backbones and side chains from a minimal connection table input. Pattern matching techniques are used to identify standard residue names and orderings in the output PDB file format.
From Open text mining solutions to Open Data resourcesdan2097
OPSIN (Open Parser for Systematic IUPAC nomenclature) has developed into a mature solution for chemical name to structure conversion. Together with other Open Source utilities such as OSCAR4, ChemSpot, and ChemicalTagger, we now have the tools to address many of the problems in chemical text mining. This ecosystem of tools has facilitated the extraction of over a million reactions, from the US patent literature, which are now available freely to all under CC-Zero. I will describe advances in OPSIN, how reactions can be extracted from text, and present some interesting analyses that are made possible by the public availability of this dataset.
Tackling the difficult areas of chemical entity extraction: Misspelt chemical...dan2097
Extracting the structures of small molecules from unstructured text is now a mature field, however there still remain areas that present considerable difficulty or have until this point remained unexplored.
One such area is identification of chemical names with misspellings or errors introduced by optical character recognition. The approach we have taken employs a formal grammar describing the syntax of a systematic name. To provide coverage over the vast majority of organic nomenclature including carbohydrates, amino acids and natural products we have developed a new way of representing the grammar such as to allow an order of magnitude more states than previous efforts1 whilst simultaneously reducing memory consumption. To efficiently perform spelling correction against this grammar we will describe a heuristic spelling correction algorithm.
Another area that remains underexplored is the identification and resolution of chemical line formulae by which we also include domain specific line formulae such as are used to describe oligosaccharides and peptides. We describe the recognition and resolution of these often overlooked chemical entities.
We also show how one can identify entities such as journal and patent references, which can aid in the navigation of semantically enhanced documents.
(1) Sayle, R.; Xie, P. H.; Muresan, S. Improved Chemical Text Mining of Patents with Infinite Dictionaries and Automatic Spelling Correction. J. Chem. Inf. Model. 2011, 52, 51–62.
OPSIN: Taming the jungle of IUPAC chemical nomenclaturedan2097
OPSIN (Open Parser for Systematic IUPAC Nomenclature) is an open source freely available program for converting chemical names, especially those that are systematic in nature, to chemical structures. The software is available as a Java library, command-line interface and as a web service (opsin.ch.cam.ac.uk). OPSIN accepts names that conform to either IUPAC or CAS nomenclature and can convert them to SMILES, InChI and CML (Chemical Markup Language).
OPSIN has grown from covering only simple general organic chemical nomenclature to the point of having competent coverage of all areas of organic chemical nomenclature. One of the most recent additions is comprehensive support for the nomenclature of carbohydrates. This brings support for dialdoses, diketoses, ketoaldoses, alditols, aldonic acids, uronic acids, aldaric acids, glycosides and oligosacchardides, in both the open chain and cyclic forms, named systematically or from trivial sugar stems with support for modification terms such as anhydro or deoxy.
OPSIN’s support for specialised and general organic nomenclature will be demonstrated through illustrative examples and accompanying performance metrics. We focus in particular on areas of nomenclature for which support was recently added and those that are complex to implement such as fused ring nomenclature.
OPSIN: Taming the Jungle of IUPAC Chemical Nomenclaturedan2097
OPSIN is a software that converts systematic chemical names found in literature and patents into chemical structures. It uses various algorithms to handle complex names involving stereochemistry, fused ring systems, and other structural features. OPSIN provides high accuracy and speed in parsing names and generates standard chemical file formats like SMILES, InChI, and CML from input names. It is widely used in applications like text mining and cheminformatics.
InChI vs IUPAC nomenclature: Aspects to be aware of when using Standard InChIdan2097
Features of IUPAC nomenclature that cannot be represented in Standard InChI will be examined to draw caution to cases where the use of standard InChI (and even in some cases non-standard InChI) may result in a loss of information. These areas include the representation of tautomers and mixtures of stereoisomers.
Automated Extraction of Reactions from the Patent Literaturedan2097
We have created a pipeline of recently enhanced open source components for extracting chemical reactions from full text chemical literature. OSCAR4 is used to recognise chemical entities and resolve to structures where appropriate. OPSIN is used to resolve systematic chemical names to structures. Chemical Tagger performs part of speech tagging allowing the interpretation of phrases in chemical syntheses. The final output is a semantic representation (chemical components and their roles, reaction conditions, actions including workup, yield and properties of the product). We then attempt to map all atoms in the product(s) to reactants. If successful we also attempt to calculate the stoichiometry of the reaction. The system has been deployed on over 56,000 USPTO patents published since 2008. The level of recall is useful and most extracted reactions make chemical sense. The pipeline is generally applicable to reactions in chemical literature including journals and theses.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
A Comprehensive Guide to DeFi Development Services in 2024Intelisync
DeFi represents a paradigm shift in the financial industry. Instead of relying on traditional, centralized institutions like banks, DeFi leverages blockchain technology to create a decentralized network of financial services. This means that financial transactions can occur directly between parties, without intermediaries, using smart contracts on platforms like Ethereum.
In 2024, we are witnessing an explosion of new DeFi projects and protocols, each pushing the boundaries of what’s possible in finance.
In summary, DeFi in 2024 is not just a trend; it’s a revolution that democratizes finance, enhances security and transparency, and fosters continuous innovation. As we proceed through this presentation, we'll explore the various components and services of DeFi in detail, shedding light on how they are transforming the financial landscape.
At Intelisync, we specialize in providing comprehensive DeFi development services tailored to meet the unique needs of our clients. From smart contract development to dApp creation and security audits, we ensure that your DeFi project is built with innovation, security, and scalability in mind. Trust Intelisync to guide you through the intricate landscape of decentralized finance and unlock the full potential of blockchain technology.
Ready to take your DeFi project to the next level? Partner with Intelisync for expert DeFi development services today!
More Related Content
Similar to Evaluating the Quality and Performance of Automatic Atom Mapping Algorithms
mcule.com is a public web service for drug discovery based in Budapest, Hungary. It provides an up-to-date compound database that can be searched simply or with complex queries, integrated workflows for virtual screening, and the ability to order compounds from multiple suppliers in a single package. The service aims to offer unlimited computational capacity through cloud computing.
Chemical Text Mining for Current Awareness of Pharmaceutical PatentsNextMove Software
This document summarizes a presentation given at the ACS National Meeting in Philadelphia on August 19th, 2012 about chemical text mining of pharmaceutical patents. The presentation discussed trends in US patent applications for pharmaceuticals from 2002-2012, workflows for extracting and analyzing information from patent texts, and tools like LeadMine and PatFetch that can recognize chemical entities and access patent texts programmatically.
Recent improvements in marvin v6 reaction atom mapping and its application to...NextMove Software
Automatic atom mapping attempts to determine the correspondence between the atoms of the reactants and products of a chemical reaction. Such mappings are useful for allowing greater specificity in queries of reaction databases. Recently there has been increased interest in their use to assist in the validation and standardisation of reactions in pharmaceutical ELNs (electronic lab notebooks). Atom mappings can, for example, detect if a reactant is missing or if a reactant does not contribute atoms to the product and hence may be better stored as an agent.
We have evaluated the performance of the new atom mapping algorithm introduced with Marvin v6 compared to the prior version on a publically available dataset extracted from the patent literature and on reactions from multiple pharmaceutical ELNs. Dramatic improvements are observed in all cases both in the percentage of reactions that can be successfully atom-mapped and the quality of mappings produced.
Finally we examine the difficulties that remain in validating reactions for which a complete atom mapping is not possible, such as for “routine” reactions where the reactant that was added is missing.
The document summarizes a presentation about green chemistry and engineering given by Ken Rollins to the American Institute of Chemical Engineers – Delaware Valley Section. It discusses the 12 principles of green chemistry, which focus on preventing waste, using safer and renewable materials, and designing for reduced environmental impact. It also outlines the 12 principles of green engineering, including ensuring inherent safety. The presentation provides examples of applying these principles, such as using catalytic reactions instead of excess reagents, and assessing solvents based on their safety and environmental impact ratings.
Yale University has transformed its former pharmaceutical campus into a research hub known as Yale West Campus. The 136-acre campus contains over 1.6 million square feet of research labs, administrative offices, and specialty storage facilities. Yale aims to establish interdisciplinary institutes that bring together faculty from across the university to work on challenges in health, environment and energy. The director of research technology discusses challenges in integrating the new campus, developing its identity and vision, and planning state-of-the-art research facilities. Several case studies highlight how old buildings have been repurposed and new centers designed to foster collaboration among researchers.
Integrating Analyzers with Automation Systems: Oil and Gas by David SchihabelISA Interchange
The document discusses how gas analyzers are integrated with automation systems for real-time control of oil and gas operations. It describes a system that currently produces 40,000 bbls of oil, 20,000 bbls of natural gas liquids, and 230 million standard cubic feet per day of natural gas. The quality of gas streams is maintained through real-time analysis of the permeate gas stream, as off-spec gas could shut down the entire production system. It also details a gas treating unit that removes CO2 from residue gas streams using analyzer results to control inlet and outlet blending valves for the single operating column.
The document discusses green chemistry and engineering principles presented by Ken Rollins at the American Institute of Chemical Engineers. It outlines the 12 principles of green chemistry which focus on preventing waste, safer chemicals and syntheses, renewable resources, energy efficiency and more. It also discusses the 12 principles of green engineering, such as ensuring inherent safety, preventing waste, maximizing efficiencies and integrating material and energy flows. The talk provided an overview of green chemistry and engineering concepts aimed at minimizing environmental impact.
Virtual Reaction Service Using Chem Axon Reactor July06DanielSButler
The document discusses implementing chemical reactions virtually using a software called Reactor. It provides examples of developing aromatic, heterocyclic, and amide reactions virtually and applying charge and pKa plugins. It also discusses considerations for accurately translating real reactions to the virtual world, including regioselectivity, stereochemistry, and resolving molecules to comprehensively cover chemical space.
Efficient Perception of Proteins and Nucleic Acids from Atomic ConnectivityNextMove Software
This document summarizes a presentation about efficiently perceiving and depicting proteins and nucleic acids from atomic connectivity data. It discusses challenges in bridging cheminformatics and bioinformatics for peptides. The presentation describes algorithms for recognizing biomolecule backbones and side chains from a minimal connection table input. Pattern matching techniques are used to identify standard residue names and orderings in the output PDB file format.
Similar to Evaluating the Quality and Performance of Automatic Atom Mapping Algorithms (11)
From Open text mining solutions to Open Data resourcesdan2097
OPSIN (Open Parser for Systematic IUPAC nomenclature) has developed into a mature solution for chemical name to structure conversion. Together with other Open Source utilities such as OSCAR4, ChemSpot, and ChemicalTagger, we now have the tools to address many of the problems in chemical text mining. This ecosystem of tools has facilitated the extraction of over a million reactions, from the US patent literature, which are now available freely to all under CC-Zero. I will describe advances in OPSIN, how reactions can be extracted from text, and present some interesting analyses that are made possible by the public availability of this dataset.
Tackling the difficult areas of chemical entity extraction: Misspelt chemical...dan2097
Extracting the structures of small molecules from unstructured text is now a mature field, however there still remain areas that present considerable difficulty or have until this point remained unexplored.
One such area is identification of chemical names with misspellings or errors introduced by optical character recognition. The approach we have taken employs a formal grammar describing the syntax of a systematic name. To provide coverage over the vast majority of organic nomenclature including carbohydrates, amino acids and natural products we have developed a new way of representing the grammar such as to allow an order of magnitude more states than previous efforts1 whilst simultaneously reducing memory consumption. To efficiently perform spelling correction against this grammar we will describe a heuristic spelling correction algorithm.
Another area that remains underexplored is the identification and resolution of chemical line formulae by which we also include domain specific line formulae such as are used to describe oligosaccharides and peptides. We describe the recognition and resolution of these often overlooked chemical entities.
We also show how one can identify entities such as journal and patent references, which can aid in the navigation of semantically enhanced documents.
(1) Sayle, R.; Xie, P. H.; Muresan, S. Improved Chemical Text Mining of Patents with Infinite Dictionaries and Automatic Spelling Correction. J. Chem. Inf. Model. 2011, 52, 51–62.
OPSIN: Taming the jungle of IUPAC chemical nomenclaturedan2097
OPSIN (Open Parser for Systematic IUPAC Nomenclature) is an open source freely available program for converting chemical names, especially those that are systematic in nature, to chemical structures. The software is available as a Java library, command-line interface and as a web service (opsin.ch.cam.ac.uk). OPSIN accepts names that conform to either IUPAC or CAS nomenclature and can convert them to SMILES, InChI and CML (Chemical Markup Language).
OPSIN has grown from covering only simple general organic chemical nomenclature to the point of having competent coverage of all areas of organic chemical nomenclature. One of the most recent additions is comprehensive support for the nomenclature of carbohydrates. This brings support for dialdoses, diketoses, ketoaldoses, alditols, aldonic acids, uronic acids, aldaric acids, glycosides and oligosacchardides, in both the open chain and cyclic forms, named systematically or from trivial sugar stems with support for modification terms such as anhydro or deoxy.
OPSIN’s support for specialised and general organic nomenclature will be demonstrated through illustrative examples and accompanying performance metrics. We focus in particular on areas of nomenclature for which support was recently added and those that are complex to implement such as fused ring nomenclature.
OPSIN: Taming the Jungle of IUPAC Chemical Nomenclaturedan2097
OPSIN is a software that converts systematic chemical names found in literature and patents into chemical structures. It uses various algorithms to handle complex names involving stereochemistry, fused ring systems, and other structural features. OPSIN provides high accuracy and speed in parsing names and generates standard chemical file formats like SMILES, InChI, and CML from input names. It is widely used in applications like text mining and cheminformatics.
InChI vs IUPAC nomenclature: Aspects to be aware of when using Standard InChIdan2097
Features of IUPAC nomenclature that cannot be represented in Standard InChI will be examined to draw caution to cases where the use of standard InChI (and even in some cases non-standard InChI) may result in a loss of information. These areas include the representation of tautomers and mixtures of stereoisomers.
Automated Extraction of Reactions from the Patent Literaturedan2097
We have created a pipeline of recently enhanced open source components for extracting chemical reactions from full text chemical literature. OSCAR4 is used to recognise chemical entities and resolve to structures where appropriate. OPSIN is used to resolve systematic chemical names to structures. Chemical Tagger performs part of speech tagging allowing the interpretation of phrases in chemical syntheses. The final output is a semantic representation (chemical components and their roles, reaction conditions, actions including workup, yield and properties of the product). We then attempt to map all atoms in the product(s) to reactants. If successful we also attempt to calculate the stoichiometry of the reaction. The system has been deployed on over 56,000 USPTO patents published since 2008. The level of recall is useful and most extracted reactions make chemical sense. The pipeline is generally applicable to reactions in chemical literature including journals and theses.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
A Comprehensive Guide to DeFi Development Services in 2024Intelisync
DeFi represents a paradigm shift in the financial industry. Instead of relying on traditional, centralized institutions like banks, DeFi leverages blockchain technology to create a decentralized network of financial services. This means that financial transactions can occur directly between parties, without intermediaries, using smart contracts on platforms like Ethereum.
In 2024, we are witnessing an explosion of new DeFi projects and protocols, each pushing the boundaries of what’s possible in finance.
In summary, DeFi in 2024 is not just a trend; it’s a revolution that democratizes finance, enhances security and transparency, and fosters continuous innovation. As we proceed through this presentation, we'll explore the various components and services of DeFi in detail, shedding light on how they are transforming the financial landscape.
At Intelisync, we specialize in providing comprehensive DeFi development services tailored to meet the unique needs of our clients. From smart contract development to dApp creation and security audits, we ensure that your DeFi project is built with innovation, security, and scalability in mind. Trust Intelisync to guide you through the intricate landscape of decentralized finance and unlock the full potential of blockchain technology.
Ready to take your DeFi project to the next level? Partner with Intelisync for expert DeFi development services today!
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...alexjohnson7307
Predictive maintenance is a proactive approach that anticipates equipment failures before they happen. At the forefront of this innovative strategy is Artificial Intelligence (AI), which brings unprecedented precision and efficiency. AI in predictive maintenance is transforming industries by reducing downtime, minimizing costs, and enhancing productivity.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Generating privacy-protected synthetic data using Secludy and Milvus
Evaluating the Quality and Performance of Automatic Atom Mapping Algorithms
1. Evaluating the Quality and
Performance of Automatic Atom
Mapping Algorithms
Daniel Lowe and Roger Sayle
NextMove Software
Cambridge, UK
ACS National Meeting, Philadelphia, USA 20th August 2012
2. What is Atom-Mapping?
Mapping
algorithm
ACS National Meeting, Philadelphia, USA 20th August 2012
3. Why Perform Atom-Mapping?
• Assigning roles to reagents
• Normalization of reactions for registration
ACS National Meeting, Philadelphia, USA 20th August 2012
4. Why Perform Atom-Mapping?
• More precise database searches
– Solvents/catalysts can be distinguished from
reactants
– Allows the relationship between the reactant
atoms and product atoms to be made explicit
ACS National Meeting, Philadelphia, USA 20th August 2012
5. Example
• I want to find reactions converting an alkene
to a cyclopropane so I search for C=C>>C1CC1
ACS National Meeting, Philadelphia, USA 20th August 2012
6. Why Perform Atom-Mapping?
• Identifying suspect reactions:
ACS National Meeting, Philadelphia, USA 20th August 2012
7. Qualities to look for in an atom
mapping algorithm
• Chemically plausible atom mappings
• Ability to distinguish genuine reactants from
solvents/catalysts
• Support for unbalanced reactions
– Side product not specified
– Reactant stoichiometry > 1
• Fast run-time
ACS National Meeting, Philadelphia, USA 20th August 2012
8. Algorithms Evaluated
Vendor:Program Version
ChemAxon:Marvin 5.10.1
GGA:Indigo 1.1
InfoChem:ICMAP 5.10
PerkinElmer:ChemDraw Ultra 12.0
ACS National Meeting, Philadelphia, USA 20th August 2012
9. Methodology
Test set Reactions
Pharmaceutical ELN subset 18,244
ChemReact68 database 67,926
SPRESI database subset 5,230
Reactions extracted from 2008- 562,872
2011 USPTO patent applications*
* Lowe, D. M. Automated Extraction of Reactions from the Patent Literature.
243rd ACS National Meeting & Exposition, San Diego, CA, March 27, 2012.
ACS National Meeting, Philadelphia, USA 20th August 2012
10. Methodology-cont.
• Reaction SMILES were used as input and
output for all algorithms bar ICMAP
• Input and output was converted to and from
RDF for use with ICMAP
• Indigo was ran with its default configuration
and more lenient settings for matching
valences, charges and bond orders
• Marvin was configured to use its best
quality mapping strategy
ACS National Meeting, Philadelphia, USA 20th August 2012
11. Ability to map all product atoms
ACS National Meeting, Philadelphia, USA 20th August 2012
19. Reuse of reactants
Marvin
ACS National Meeting, Philadelphia, USA 20th August 2012
20. Reuse of reactants
ChemDraw
ACS National Meeting, Philadelphia, USA 20th August 2012
21. Reuse of reactants
Indigo
ACS National Meeting, Philadelphia, USA 20th August 2012
22. Reuse of reactants
ICMAP
ACS National Meeting, Philadelphia, USA 20th August 2012
23. Single Atom Mapping
ICMAP/Marvin
ChemDraw/Indigo
ACS National Meeting, Philadelphia, USA 20th August 2012
24. Bugs and quirks
• Marvin
– 2 unsuccessful mappings produced unchecked
exceptions rather than checked exceptions
• ChemDraw
– Hydrogen on aromatic atoms missing in SMILES
output
• Indigo
– Calculation of valency fails for aromatic sulfur
ACS National Meeting, Philadelphia, USA 20th August 2012
25. Bugs and quirks
• ICMAP
– Single atom products are interpreted as empty
molecules or occasionally replaced by a product
from a previous reaction (bug reported)
– Input files must be < 2gb and use dos line endings
ACS National Meeting, Philadelphia, USA 20th August 2012
26. conclusions
• ICMAP produced the best quality mappings on
the tested sets
• Atom mapping isn’t as simple as finding a
maximum common subgraph mapping
• In all the algorithms there were aspects that
could be improved to yield appreciable
benefits
ACS National Meeting, Philadelphia, USA 20th August 2012
27. acknowledgements
• Ed Griffen and Nick Tomkinson, AstraZeneca.
• Andrew Wooster, GSK.
• Hans Kraut, InfoChem
• Thank you for your time.
ACS National Meeting, Philadelphia, USA 20th August 2012