I have published a new preprint:

[p2] Ritchie JB, Frey L, Lamy JB, Bellcross C, Morrison H, Schiffman JD, Welch BM. Enabling patients to receive clinical practice guideline recommendations for hereditary cancer risk using chatbots, family history, application programming interfaces (API), ontologies, and Owlready2: System description. Preprint 2021

Owlready is a Python module for ontology-oriented programming. It can load OWL 2.0 ontologies and manipulate them transparently in Python.

Here are the changes:

• Bugfixes: - Fix installation as a requirement of another Python module

The new version be downloaded from PyPI (Python Package Index): https://pypi.python.org/pypi/Owlready2

Owlready is a Python module for ontology-oriented programming. It can load OWL 2.0 ontologies and manipulate them transparently in Python.

This version fix an installation problem under Windows, and also improve the execution of reasoners under Windows (no more DOS windows).

Here are the changes:

• Fix installation under Windows (contributed by CVK)

• Under Windows, run the reasoners without opening a DOS windows

The new version be downloaded from PyPI (Python Package Index): https://pypi.python.org/pypi/Owlready2

Owlready is a Python module for ontology-oriented programming. It can load OWL 2.0 ontologies and manipulate them transparently in Python.

Here are the changes:

• When Pellet is called with debug >= 2 on an inconsistent ontology, Pellet explain output is displayed (contributed by Carsten Knoll)

• Update doc theme (contributed by Carsten Knoll)

• Adapt setup.py to allow 'python setup.py develop' and 'pip install -e .' (contributed by Carsten Knoll)

• Add 'url' argument to Ontology.load() method

• Add 'read_only' argument to World.set_backend() method

• Bugfixes: - Fix XML/RDF file parsing/writing for entity having ':' in their name - Fix destroy_entity(), was leaking some RDF triples when class contructs or equivalent_to were involved - Fix 'Class1(entityname); Class2(entityname)' (was changing the individual namespace) - Fix annotation request on RDF annotation properties, e.g. label.label

The new version be downloaded from PyPI (Python Package Index): https://pypi.python.org/pypi/Owlready2

I presented my work on data science and drug safety: visual mining of adverse drug events observed in clinical trials of pain treatments.

Slides are available here (in French), the preprint that describes the study here (in English), the online platform here (in English and French) and the video of the seminar here (in French)!

My book "Ontologies with Python" has just been published by Apress editions.

This 350-pages book describes how to use OWL 2.0 ontologies in Python 3.x, with the Owlready2 Python module for ontology-oriented programming.

Use ontologies in Python, with the Owlready2 module developed for ontology-oriented programming. You will start with an introduction and refresher on Python and OWL ontologies. Then, you will dive straight into how to access, create, and modify ontologies in Python. Next, you will move on to an overview of semantic constructs and class properties followed by how to perform automatic reasoning. You will also learn about annotations, multilingual texts, and how to add Python methods to OWL classes and ontologies. Using medical terminologies as well as direct access to RDF triples is also covered.

Python is one of the most used programming languages, especially in the biomedical field, and formal ontologies are also widely used. However, there are limited resources for the use of ontologies in Python. Owlready2, downloaded more than 60,000 times, is a response to this problem, and this book is the first one on the topic of using ontologies with Python.

What You Will Learn:

• Use Owlready2 to access and modify OWL ontologies in Python

• Publish ontologies on dynamic websites

• Perform automatic reasoning in Python

• Use well-known ontologies, including DBpedia and Gene Ontology, and terminological resources, such as UMLS (Unified Medical Language System)

• Integrate Python methods in OWL ontologies

Who Is This Book For: Beginner to experienced readers from biomedical sciences and artificial intelligence fields would find the book useful.

The book is an updated translation of the French book "Python et les ontologies" published at ENI éditions last year.

More informations on the editor website:

https://www.apress.com/fr/book/9781484265512

Owlready is a Python module for ontology-oriented programming. It can load OWL 2.0 ontologies and manipulate them transparently in Python.

This new release includes a new module for displaying entities in Description Logics (DL), and bugfixes.

Here are the changes:

• Module owlready2.dl_render allows rendering entities to Description Logics (contributed by Simon Bin)

• Bugfixes: - Adjustment in the comparison of strings from SameAs and DiferrentFrom, allowing equal comparison regardless of the case-sensitive (contributed by Thiago Feijó) - Fix transitive equivalent_to relations between classes and OWL constructs - Fix AnnotationProperty[entity] where entity is a predefined OWL entity (e.g. comment or Thing) - Fix entity.AnnotationProperty where entity is a predefined OWL entity (e.g. comment or Thing) - Fix HermiT when reasoning on several ontologies with imports statement - Ignore "A type A", with a warning

The new version be downloaded from PyPI (Python Package Index): https://pypi.python.org/pypi/Owlready2

Owlready is a Python module for ontology-oriented programming. It can load OWL 2.0 ontologies and manipulate them transparently in Python.

This new release includes a few new features, and bugfixes.

Here are the changes:

• Allow the declaration of custom datatypes with declare_datatype()

• Support the annotation of annotations (e.g. a comment on a comment)

• search() now support the "subproperty_of" argument

• search() now support the "bm25" argument (for full-text searches)

• Bugfixes: - Fix Concept.descendant_concepts() in PymedTermino2 - Update already loaded properties when new ontologies are loaded - Now accept %xx quoted characters in file:// URL - Improve error message on punned entities - Property.get_relations() now considers inverse properties - Fix "AttributeError: 'mappingproxy' object has no attribute 'pop'" error - Fix Thing.instances()

The new version be downloaded from PyPI (Python Package Index): https://pypi.python.org/pypi/Owlready2

I have published a new journal paper:

[j64] Mbaye F, Lamy JB, Sembene M. Identifying the mitochondrial DNA mutations that cause cancer. Research Outbreak 2020;117:50-53

I have published a new journal paper:

[j63] Marcilly R, Douze L, Ferré S, Audeh B, Bobed C, Lillo-Le Louët A, Lamy JB, Bousquet C. How to interact with medical terminologies? Formative usability evaluations comparing three approaches for supporting the use of MedDRA by pharmacovigilance specialists. BMC Medical Informatics and Decision Making 2020;20:261

I presented my works at the Information Visualisation (iV) 2020 conference.

The paper is entitled "Comparison of four visual analytics techniques for the visualization of adverse drug event rates in clinical trials" and is available here and the presentation there or in video below:

iv2020_video.mp4

I presented my works on the use of rainbow boxes for determining synergies between drugs, at ICIMTH 2020.

My paper was entitled "Visualization of potential drug synergies". It is available here and the presentation just below in video:

icimth_video.mp4

And I obtained a Best paper award!

My students and colleagues also presented four papers:

• Saab A, Saikali M, Lamy JB: Comparison of machine learning algorithms for classifying adverse-event related 30-day hospital readmissions: Potential implications for patient safety

• Diallo AH, Camara G, Lo M, Diagne I, Lamy JB: Iconic visualization of sickle cell patients current and past health status

• Mouazer A, Sedki K, Tsopra R, Lamy JB: Visualization of drug interactions for supporting medication review

• Sedki K, Lakrafli C, Lamy JB, Tsopra R: An approach based on preference learning for identifying experts reasoning in antibiotic treatment

I have published a new journal paper:

[j60] Bouaud J, Pelayo S, Lamy JB, Prébet C, Ngo C, Teixeira L, Guezennec G, Séroussi B. Implementation of an ontological reasoning to support the guideline-based management of primary breast cancer patients in the DESIREE project. Artificial Intelligence in Medicine 2020;108:101922