CINF66 Visualizing Molecules In and Out of Context
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This document discusses using data science techniques to recommend related molecules based on different contexts. It describes analyzing chemical similarity based on molecular structure, related papers in literature, and user behavior data. The approaches were validated by comparing automatically grouped molecule clusters to known clusters in literature and behavior datasets. Recommendations based on fingerprint similarities worked best to predict both literature and behavior relatedness. Going forward, the team aims to develop a molecular recommender system that presents molecules in different contexts and improve their system for extracting chemical entities from text.
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Sybrandt Thesis Proposal Presentation
The document is a thesis proposal by Justin Sybrandt at Clemson University that outlines his past and proposed work on exploiting latent features in text and graphs. It summarizes Sybrandt's peer-reviewed work using embeddings to generate biomedical hypotheses from text and validate hypotheses through ranking. It also discusses pending work on heterogeneous bipartite graph embeddings and partitioned hypergraphs. The proposal provides background on Sybrandt's hypothesis generation work and outlines his proposed future research directions involving graph embeddings.
eScience at the Royal Society of Chemistry and our current initiatives
eScience at the Royal Society of Chemistry and our current initiativesUS Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Access to scientific information has changed in a manner that was likely never even imagined by the early pioneers of the internet. The quantities of data, the array of tools available to search and analyze, the devices and the shift in community participation continues to expand while the pace of change does not appear to be slowing. ChemSpider is one of the chemistry community’s primary online public compound databases. Containing tens of millions of chemical compounds and its associated data ChemSpider serves data tens of thousands of chemists every day and it serves as the foundation for many important international projects to integrate chemistry and biology data, facilitate drug discovery efforts and help to identify new chemicals from under the ocean. This presentation will provide an overview of the expanding reach of this eScience cheminformatics platform and the nature of the solutions that it helps to enable including structure validation, text mining and semantic markup, the National Chemical Database Service for the United Kingdom and the development of a chemistry data repository. We will also discuss the possibilities it offers in the domain of crowdsourcing and open data sharing. The future of scientific information and communication will be underpinned by these efforts, influenced by increasing participation from the scientific community and facilitated collaboration and ultimately accelerate scientific progress.eScience Resources for the Chemistry Community from the Royal Society of Chem...
eScience Resources for the Chemistry Community from the Royal Society of Chem...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Our access to scientific information has changed in ways that were hardly imagined even by the early pioneers of the internet. The immense quantities of data and the array of tools available to search and analyze online content continues to expand while the pace of change does not appear to be slowing. ChemSpider is one of the chemistry community’s primary online public compound databases. Containing tens of millions of chemical compounds and its associated data ChemSpider serves data tens of thousands of chemists every day and it serves as the foundation for many important international projects to integrate chemistry and biology data, facilitate drug discovery efforts and help to identify new chemicals from under the ocean. This presentation will provide an overview of the expanding reach of the ChemSpider platform and the nature of the solutions that it helps to enable. We will also discuss the possibilities it offers in the domain of crowdsourcing and open data sharing. The future of scientific information and communication will be underpinned by these efforts, influenced by increasing participation from the scientific community and facilitated collaboration and ultimately accelerate scientific progress.Hosting public domain chemicals data online for the community – the challenge...
Hosting public domain chemicals data online for the community – the challenge...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The Royal Society of Chemistry hosts one of the worlds’ richest collections of online chemistry data that is free-to-access for the community. ChemSpider presently hosts over 30 million unique chemical compounds together with associated data and accessible via a number of search techniques. With almost 50,000 unique users per day from around the world the site offers scientists the ability to investigate the world of small molecules via property searches, analytical data and predictive models. The challenges associated with providing a similar platform for “materials” are manifold but, if they could be addressed, would offer a valuable service to the materials community. This presentation will provide an overview of how ChemSpider was built, our efforts to expand the capabilities to a more encompassing data repository and some of the challenges faced to embrace the diverse world of materials informatics and online data access.Virtual Screening in Drug Discovery
Virtual screening uses computer-based methods to filter large databases of chemical compounds to identify a subset of compounds that are most likely to bind to and activate a target linked to a disease. It helps address the challenge of exploring the vast chemical space compared to the limited number of compounds that can be experimentally screened. The document discusses various virtual screening methods including ligand-based approaches like similarity searching and pharmacophore modeling as well as structure-based approaches like molecular docking that predict binding orientations. It also covers best practices for applying filters to select for drug-like and lead-like compounds.
Serving the medicinal chemistry community with Royal Society of Chemistry che...
Serving the medicinal chemistry community with Royal Society of Chemistry che...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The Royal Society of Chemistry (RSC) is a major participant in providing access to chemistry related data via the web. As an internationally renowned society for the chemical sciences, a scientific publisher and the host of the ChemSpider database for the community, RSC continues to make dramatic strides in providing online access to data. ChemSpider provides access to over 30 million chemicals sourced from over 500 data suppliers and linked out to related information on the web. The platform is a crowdsourcing environment whereby members of the community can participate in validating and expanding the content of the database. With a set of application programming interfaces ChemSpider is used by various organizations and projects to serve up data for various purposes. These include structure identification for mass spectrometry instrument vendors, RSC databases such as the Marinlit natural products database and a European grant-based project from the Innovative Medicines Initiative fund. This presentation will provide an overview of various cheminformatics activities and projects that RSC is involved with to serve the medicinal chemistry community. This will include the Open PHACTS semantic web project, the PharmaSea project to identify new pharmaceutical leads from the ocean and the UK National Compound Collection to identify new lead compounds contained within PhD theses.ICIC 2013 Conference Proceedings Antony Williams Royal Society of Chemistry
The Big Data Challenges Associated with Building a National Data Repository for Chemistry
Antony Williams (Royal Society of Chemistry , USA)
At a time when the data explosion has simply been redefined as “Big”, the hurdles associated with building a subject-specific data repository for chemistry are daunting. Combining a multitude of non-standard data formats for chemicals, related properties, reactions, spectra etc., together with the confusion of licensing and embargoing, and providing for data exchange and integration with services and platforms external to the repository, the challenge is significant. This all at a time when semantic technologies are touted as the fundamental technology to enhance integration and discoverability. Funding agencies are demanding change, especially a change towards access to open data to parallel their expectations around Open Access publishing. The Royal Society of Chemistry has been funded by the Engineering and Physical Science Research of the UK to deliver a “chemical database service” for UK scientists. This presentation will provide an overview of the challenges associated with this project and our progress in delivering a chemistry repository capable of handling the complex data types associated with chemistry. The benefits of such a repository in terms of providing data to develop prediction models to further enable scientific discovery will be discussed and the potential impact on the future of scientific publishing will also be examined.
Big data challenges associated with building a national data repository for c...
Big data challenges associated with building a national data repository for c...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
At a time when the data explosion has simply been redefined as “Big”, the hurdles associated with building a subject-specific data repository for chemistry are daunting. Combining a multitude of non-standard data formats for chemicals, related properties, reactions, spectra etc., together with the confusion of licensing and embargoing, and providing for data exchange and integration with services and platforms external to the repository, the challenge is significant. This all at a time when semantic technologies are touted as the fundamental technology to enhance integration and discoverability. Funding agencies are demanding change, especially a change towards access to open data to parallel their expectations around Open Access publishing. The Royal Society of Chemistry has been funded by the Engineering and Physical Science Research of the UK to deliver a “chemical database service” for UK scientists. This presentation will provide an overview of the challenges associated with this project and our progress in delivering a chemistry repository capable of handling the complex data types ssociated with chemistry. The benefits of such a repository in terms of providing data to develop prediction models to further enable scientific discovery will be discussed and the potential impact on the future of scientific publishing will also be examined. Our dire need to mandate data standards and expectations for scientific publi...
Our dire need to mandate data standards and expectations for scientific publi...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The document discusses the need for mandating data standards and open sharing in scientific publishing. It notes the loss of data reproducibility due to a lack of standardized data formats. The author advocates that publishers should require authors to register chemical compounds, submit spectral data in standard digital formats rather than images, and make data openly available with metadata and provenance. Adopting standards like CVSP could help validate structures and spectra before publication. While mandates may not be preferred, open data standards are important for scientific progress and reproducibility.Bio inspiring computing and its application in cheminformatics
This document discusses applying bio-inspired computing techniques to problems in cheminformatics. It begins with introductions to cheminformatics and bio-inspired computing. Popular bio-inspired algorithms like ant colony optimization are explained. The document outlines applications of bio-inspired approaches to tasks in cheminformatics like classification, clustering, and feature selection. It concludes by noting potential applications in drug discovery and design.
Automated workflows for data curation and standardization of chemical structu...
This document summarizes an automated workflow for standardizing chemical structures for use in QSAR modeling. It describes the steps taken to clean a dataset of over 15,000 chemicals with LogP values, which included removing duplicates, normalizing tautomers, filtering out inorganics and mixtures, and standardizing structures. The workflow generates InChI keys, canonical SMILES and 2D/3D descriptors to produce "QSAR-ready" structures. The standardized structures have been used successfully in developing OPERA models for androgen receptor activity and endocrine disruption screening.
The research process steps
The document outlines the key steps in the research process, including developing the research project, reviewing literature, creating a research proposal, conducting a pilot study, and project management. It discusses developing a research question and aims, reviewing background literature and gaps, designing methodology, and plans for analysis, reporting, and writing up results. Methods of searching literature systematically using databases and evaluating sources are also covered. The importance of a pilot study and a clear timetable for the research proposal and project are emphasized.
Accessing Environmental Chemistry Data via Data Dashboards and Applications t...
Accessing Environmental Chemistry Data via Data Dashboards and Applications t...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The document summarizes a presentation about accessing environmental chemistry data through data dashboards and applications to mass spectrometry non-targeted analysis. It introduces the CompTox Chemicals Dashboard, which provides data on over 1.2 million chemicals. It describes how the dashboard supports mass spectrometry analysis and efforts to build databases of analytical methods and experimental spectra to help with identification. Sources of data and ongoing work to curate additional documents and spectra are also summarized.Virtual screening techniques
This document summarizes various virtual screening techniques used in drug discovery. It discusses ligand-based methods like similarity searching using 2D and 3D fingerprints, pharmacophore mapping. It also discusses structure-based methods like protein-ligand docking to predict binding poses and scores. Hybrid methods combining different techniques are also used. The document provides an overview of key virtual screening methods and their applications to enrich hit rates and select compounds for further testing from large libraries in an efficient manner during the drug discovery process.
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Recently uploaded
Immersive Learning That Works: Research Grounding and Paths Forward
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
8.Isolation of pure cultures and preservation of cultures.pdf
Isolation of pure culture, its various method.
Shallowest Oil Discovery of Turkiye.pptx
The Petroleum System of the Çukurova Field - the Shallowest Oil Discovery of Türkiye, Adana
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
The pygmy halfbeak Dermogenys colletei, is known for its viviparous nature, this presents an intriguing case of relatively low fecundity, raising questions about potential compensatory reproductive strategies employed by this species. Our study delves into the examination of fecundity and the Gonadosomatic Index (GSI) in the Pygmy Halfbeak, D. colletei (Meisner, 2001), an intriguing viviparous fish indigenous to Sarawak, Borneo. We hypothesize that the Pygmy halfbeak, D. colletei, may exhibit unique reproductive adaptations to offset its low fecundity, thus enhancing its survival and fitness. To address this, we conducted a comprehensive study utilizing 28 mature female specimens of D. colletei, carefully measuring fecundity and GSI to shed light on the reproductive adaptations of this species. Our findings reveal that D. colletei indeed exhibits low fecundity, with a mean of 16.76 ± 2.01, and a mean GSI of 12.83 ± 1.27, providing crucial insights into the reproductive mechanisms at play in this species. These results underscore the existence of unique reproductive strategies in D. colletei, enabling its adaptation and persistence in Borneo's diverse aquatic ecosystems, and call for further ecological research to elucidate these mechanisms. This study lends to a better understanding of viviparous fish in Borneo and contributes to the broader field of aquatic ecology, enhancing our knowledge of species adaptations to unique ecological challenges.
The debris of the ‘last major merger’ is dynamically young
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
学校原件一模一样【微信：741003700 】《(UAM毕业证书)马德里自治大学毕业证学位证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
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Phenomics assisted breeding in crop improvement
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
ESR spectroscopy in liquid food and beverages.pptx
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
Randomised Optimisation Algorithms in DAPHNE
Slides from talk:
Aleš Zamuda: Randomised Optimisation Algorithms in DAPHNE .
Austrian-Slovenian HPC Meeting 2024 – ASHPC24, Seeblickhotel Grundlsee in Austria, 10–13 June 2024
https://ashpc.eu/
Compexometric titration/Chelatorphy titration/chelating titration
Classification
Metal ion ion indicators
Masking and demasking reagents
Estimation of Magnisium sulphate
Calcium gluconate
Complexometric Titration/ chelatometry titration/chelating titration, introduction, Types-
1.Direct Titration
2.Back Titration
3.Replacement Titration
4.Indirect Titration
Masking agent, Demasking agents
formation of complex
comparition between masking and demasking agents,
Indicators/Metal ion indicators/ Metallochromic indicators/pM indicators,
Visual Technique,PM indicators (metallochromic), Indicators of pH, Redox Indicators
Instrumental Techniques-Photometry
Potentiometry
Miscellaneous methods.
Complex titration with EDTA.
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptx
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
The cost of acquiring information by natural selection
This is a short talk that I gave at the Banff International Research Station workshop on Modeling and Theory in Population Biology. The idea is to try to understand how the burden of natural selection relates to the amount of information that selection puts into the genome.
It's based on the first part of this research paper:
The cost of information acquisition by natural selection
Ryan Seamus McGee, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, Carl T. Bergstrom
bioRxiv 2022.07.02.498577; doi: https://doi.org/10.1101/2022.07.02.498577
Equivariant neural networks and representation theory
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
Bob Reedy - Nitrate in Texas Groundwater.pdf
Presented at June 6-7 Texas Alliance of Groundwater Districts Business Meeting
Recently uploaded (20)
Immersive Learning That Works: Research Grounding and Paths Forward
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8.Isolation of pure cultures and preservation of cultures.pdf
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Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
The debris of the ‘last major merger’ is dynamically young
The debris of the ‘last major merger’ is dynamically young
Basics of crystallography, crystal systems, classes and different forms
Basics of crystallography, crystal systems, classes and different forms
ESR spectroscopy in liquid food and beverages.pptx
ESR spectroscopy in liquid food and beverages.pptx
Compexometric titration/Chelatorphy titration/chelating titration
Compexometric titration/Chelatorphy titration/chelating titration
aziz sancar nobel prize winner: from mardin to nobel
aziz sancar nobel prize winner: from mardin to nobel
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptx
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptx
The cost of acquiring information by natural selection
The cost of acquiring information by natural selection
Equivariant neural networks and representation theory
Equivariant neural networks and representation theory
CINF66 Visualizing Molecules In and Out of Context
- 1. Visualizing Molecules In and Out of Context Jeff White PhD
- 2. • Professional body • Not for profit • Chemical science education • World-class publisher Royal Society of Chemistry
- 3. • Drive RSC mission • Community focussed • Evidence-based decisions Data Science at the RSC
- 4. What do we work on? Tech Development • Data processing pipeline • Term extraction from literature Applications • Citation velocity • Recommending papers Cheminformatics • Molecular characterisation • Chemical similarity Business analytics • Lead generation • Data dashboards
- 5. Recommending Molecules • Identifying context • Validating approach • Placing in context • Related work • Going forward
- 8. Identifying chemical context What other molecules are “related” to vancomycin? Vancomycin
- 9. • Computed similarity “X has structural features in common with...” • Published literature “papers mentioning X also mentioned...” • Human behaviour “users who looked at X also viewed...” Finding “related-ness”...
- 11. • ChemSpider web logs (2015-2016) • molecules grouped by user IDs • anonymised, aggregated Behaviour data
- 12. • RSC corpus (2000-2012) • text-mined for chemical compounds • molecules grouped by article Literature data
- 13. • Combine behaviour and literature sets • Must appear twice in both sets • Total of ca. 20K molecules Data Set
- 14. • Behaviour & Literature Mean-square contingency coefficient φ • Fingerprinting Morgan (radius = 2) & Topology Dice coefficient • Gives four similarity “ranking” data sets Methods
- 15. Validation: Permutation testing Behaviour Literature Morgan Topology Behaviour — 0.044 0.015 0.011 Literature 0.044 — 0.036 0.030 Morgan 0.015 0.036 — 0.110 Topology 0.011 0.030 0.110 —
- 16. • Distance measures for pairs of molecules • Chemicals can be clustered • Form clusters using Affinity Propagation Number of clusters decided by the process Each cluster has exemplar – the “best example” • Compare clusters Finding Clusters and Exemplars
- 17. Clusterings Ranking Behaviour Literature Morgan Topology Behaviour 0.0978 0.0739 0.0822 0.0771 Literature 0.000809 0.625 0.0956 0.0840 Morgan 0.0943 0.175 0.635 0.325 Topology 0.000608 0.000711 0.313 0.578 Validation: BEDROC measure
- 18. • For database vs. fingerprint-based similarities “clustered” Morgan fingerprints provide the best proxy for both behaviour and literature literature similarities the best overall • Methods are actually contextually distinct best used in combination • Morgan fingerprinting best for new compounds Results
- 20. azithromycin streptomycin lincomycin amoxicillin amikacin
- 21. majusculamide C petriellin A idraparinux biflorin
- 24. Related work
- 25. • Extracting chemical names from patents and other text • Using deep learning techniques – recurrent artificial neural networks • Participating in public, competitive evaluation (BioCreative V.5 Becalm) 0.9006 precision, 0.9062 recall, .9032 F Chemlistem
- 26. Going forward
- 27. • Molecular Recommender Present more “contexts” for scientists Actively working on user evaluation • Chemlistem Accurate automatic entity detection Next steps
- 28. Colin Batchelor – System design & programming Acknowledgements The Data Science team