The fusion of synthetic biology with classical materials science has yielded breakthrough innovations and spawned a new biotechnology field: engineered living (ELMs). Taxonomic classifications ELM research highlight states the art, opportunities, challenges, emerging trends. Opportunities abound to engineer bacteria, fungi, plants, mammalian cells, diverse consortia those organisms produce – pe...

This paper deals with taxonomy alignment and presents structural techniques of an alignment method suitable with a dissymmetry in the structure of the mapped taxonomies. The aim is to allow a uniform access to documents belonging to a same application domain, assuming retrieval of documents is supported by taxonomies. We applied our method to various taxonomies using our prototype, TaxoMap. Exp...

In this paper we present and compare two methodologies for rapidly inducing multiple subject-specific taxonomies from crawled data. The first method involves a sentence-level words co-occurrence frequency method for building the taxonomy, while the second involves the bootstrapping of a Word2Vec based algorithm with a directed crawler. We exploit the multilingual open-content directory of the W...

Taxonomy alignment is a way to integrate two or more taxonomies. Semantic interoperability between datasets, information systems, and knowledge bases is facilitated by combining the different input taxonomies into merged taxonomies that reconcile apparent differences or conflicts. We show how alignment problems can be solved with a logic-based region connection calculus (RCC-5) approach, using ...

Industrial taxonomies have the potential to automate information retrieval, facilitate interoperability and, most importantly, improve decision making -decisions that must comply with existing government regulations and codes of practice. However, it is difficult to find those regulations and codes most relevant to a particular decision, even though they are now in digital form, and often avail...

With the increased use of ontologies in semantically-enabled applications, the issues of debugging and aligning ontologies have become increasingly important. The quality of the results of such applications is directly dependent on the quality of the ontologies and mappings between the ontologies they employ. A key step towards achieving high quality ontologies and mappings is discovering and r...

Building very big taxonomies is a laborious task vulnerable to errors and management/scalability deficiencies. FASTAXON is a system for building very big taxonomies in a quick, flexible and scalable manner that is based on the faceted classification paradigm [4] and the Compound Term Composition Algebra [5]. Below we sketch the architecture and the functioning of this system and we report our e...

We investigate machine learning methods for automatically integrating objects from different taxonomies into a master taxonomy. This problem is not only currently pervasive on the Web, but is also important to the emerging Semantic Web. A straightforward approach to automating this process would be to build classifiers through machine learning and then use these classifiers to classify objects ...

In recent years, the number of sequences of diverse species submitted to GenBank has grown explosively and not infrequently the data contain errors. This problem is extensively recognized but not for invalid or incorrectly identified species, sample mixed-up, and contamination. DNA barcoding is a powerful tool for identifying and confirming species and one very important application involves fo...