May 032016

NEWS!!!! The Phenotype RCN has funds available to support graduate students, postdocs and other researchers and curators to attend ontology-related meetings this summer.

For example, the upcoming joint ICBO (International Conference on Biological Ontology) and BioCreative meeting (August 1 – 4, 2016; Oregon State University, Corvallis, OR, USA) would be an excellent venue to present phenotype ontology based work, as would various organismal and model-organism based meetings.

Please send an email to Andy Deans ( or Eva Huala ( if you are interested, indicating the meeting proposed, whether you are presenting, your current position (student, faculty, etc.), the amount of funds requested, and a 200-word statement regarding the value of the opportunity to you and the relationship to phenotype ontologies.

Tree of life and data integration challenges at the first FuturePhy workshop

 Phenex, Phylogenetics, Teleosts, Workshops  Comments Off on Tree of life and data integration challenges at the first FuturePhy workshop
Apr 062016

What are the challenges in building, visualizing and using the Tree of Life? How can we best utilize and build on existing phylogenetic knowledge and look ahead to address the challenges of data integration? Recently, fellow Phenoscaper Jim Balhoff and I attended the first FuturePhy workshop in Gainesville, Florida (February 20-22, 2016). The workshop brought together three taxonomically-defined working groups (catfish, beetles, barnacles) to build megatrees from existing phylogenetic studies, and identify and begin applying diverse data layers for their respective groups. Open Tree and Arbor personnel were on hand discuss and help solve issues in data integration.

The catfish team (John Lundberg, Mariangeles Arce, Jim Balhoff, Brian Sidlauskas, Ricardo Betancur, Laura Jackson, Kole Kubicek, Kyle Luckenbill, and myself, Wasila Dahdul) included participants with expertise in catfish anatomy, phylogenetics (molecular and morphological), development, bioinformatics, and digital imaging. We were motivated to build on the work of the All Catfish Species Inventory to achieve a more complete understanding of catfish diversification by integrating published phylogenies, 2D and 3D images in various online repositories, and thousands of computable phenotypes for catfishes in Phenoscape.

Screen Shot 2016-04-06 at 9.58.44 AM

We held several hands-on sessions on tree grafting (using Mesquite, R, and Arbor), data annotation (using Phenex), and tree submission to Open Tree.  We also examined an automatically generated supermatrix for 18 published catfish matrices in the Phenoscape KB (generated using the OntoTrace tool), and prototype data visualizations for supermatrices developed by Curt Lisle in Arbor. We used Mesquite to manually create a draft megatree, and in parallel, uploaded trees to Open Tree, which automatically synthesized a megatree for catfishes. Our plan is to compare the output of manual tree-building in Mesquite with the automated tree from Open Tree.

Among the issues and priorities that emerged during the workshop was the need for inclusion of the authoritative Catalog of Fishes taxonomy in Open Tree, and allowing the addition of unnamed or uncertainly identified taxa commonly used in matrices. We also discussed challenges in automated character consolidation across multiple studies, and the reuse of images across multiple online archives.

We left with a plan to continue tree building and data layer integration post-workshop, with the aim of publishing the catfish megatree (including the methods and remaining challenges) and the integration of data layers via interactions between Arbor, Open Tree, and Phenoscape.

Filed under: Phenex, Phylogenetics, Teleosts, Workshops
Apr 042016
a group of people smiling and standing in front of sculpture at Biosphere 2

Participants at the fifth and final summit meeting of the Phenotype RCN. Photo by Andy Deans (CC BY 2.0).

The Phenotype Research Coordination Network hosted its fifth and final summit meeting at the end of February at Biosphere 2, with 66(!) people in attendance. The focus was on data integration, and we were fortunate to have the FuturePhy project join us. Our program was packed, with a mix of panels, talks (we have links to slideshows), and breakout sessions that focused on proposal ideas. One frequent topic for discussion was the need to keep this network going, as there remains a clear need for outreach and mechanisms that foster collaborations on phenotype data. Several working groups also focused on large, international collaborations that would make phenotype tools, like ontologies, and phenotype data more accessible and sustainable—imagine something like GenBank but for phenotypes.

Another successful and compelling component of this meeting was the inclusion of many early career researchers and graduate students, who formed a cohesive network themselves. Their discussions and reports to the larger group identified broad needs and informed our collective ideas for future outreach directions.

The Phenotype RCN has been productive, impactful, and and incredibly rewarding. We thank all who have been involved, especially meeting participants and our advisory board. While this phase—i.e., our original NSF-funded schedule—may be winding down, the network is robust and active. Stay tuned for further developments!

 Posted by on April 4, 2016 at 4:45 pm
Jan 202016

NBO-ABO Merger Workshop Smithsonian, DC 25Oct15-620

This post is a followup to our previous post about integrating the Animal Behavior Ontology (ABO) and the NeuroBehavior Ontology (NBO). This covers the second workshop, a conference call held in early December and the poster one of us (PM) presented at SICB 2016 on January 6.

With additional funding from the Phenotype RCN, on October 24–25, 2015 we held the second workshop to begin the process of merging the ABO and the NBO based on the first workshop’s recommendations. This workshop was held at the Smithsonian Museum in Washington. Attendees included Elissa Chesler, George Gkoutos, David Osumi-Sutherland, and Reid Rumelt (Cornell undergraduate working on media tagging-based research); and workshop organizers Anne Clark, Sue Margulis, Peter Midford, Cynthia Parr, and Katja Schultz (our Local Host). Melissa Haendel participated remotely.

We made good progress getting started on a use-case based paper for applications of a behavior ontology. We also have a real home for the ABO – we deposited the OWL rendering Peter Midford generated in 2006 as the initial commit in a GitHub repository (note that this is the same repository where NBO is maintained).

We started the process of merging the ABO and NBO, our central objective. One of ABO’s strengths is a clear division between observable behavior (acts, events, and processes) and functional interpretations (for example, running vs. fleeing from a predator). The NBO is organized rather differently and we would like the division in ABO to appear at least somewhere in NBO. NBO contains a sizable number of terms not relevant to the behavioral ecology community, just as ABO has terms that are not of current use to the model organism community. We identified a number of stakeholder projects who would be affected and could potentially benefit by the merger, including Virtual Fly Brain, Rat Genome Database, and the International Mouse Phenotype consortium and probably others.

Since the workshop we have had several conference calls with the NBO developers (George Gkoutos and Robert Hoehndorf) to refine the concerns of other stakeholders. Discussion made it clear that NBO is focussed on behavior phenotypes, rather than behavior processes. However, there was some interest in incorporating the ABO functional terms. The thought was that the remaining ABO terms (those referring to events, acts, and processes) should wind up in the Gene Ontology (GO). Several of us are working on the process of merging the functional terms into NBO, and separately, looking through the existing process terms in the GO. We may want to propose a behavior process ontology, at least as a parking place for terms that eventually are added to the GO.

Finally, we presented a poster at the SICB 2016 meeting in Portland, OR on January 6. We will continue to use opportunities like this to discuss the process and implications of this merger with the broader animal behavior and neuroscience communities. We are developing a set of case studies and have outlined a followup paper to highlight both the applications of the outcome of the merging process and lessons learned during that process.

 Posted by on January 20, 2016 at 4:40 pm

Ontology-based text markup tools

 Uncategorized  Comments Off on Ontology-based text markup tools
Jan 142016

Efficiently extracting knowledge from the published literature is a challenge faced by many database projects in biology, and many of us are interested in tools that can assist and speed up the task of identifying concepts in free text. I’ve recently used two text markup tools that are helpful in keeping up with the literature and rapidly developing ontologies. As a participant in the Fifth BioCreative Challenge, in which biocurators test and evaluate text mining systems, I evaluated the EXTRACT bookmarklet tool. EXTRACT was developed for metagenomics data and provides full-page tagging of mapped terms from environment, disease, taxonomy, and tissue ontologies, and can also markup shorter selections of text on an HTML page. The tool is immediately useful, particularly during the first stages of the curation process, as a curator is surveying the literature for relevant articles.

Annotating long, descriptive text has also been a challenge for Phenoscape. To assist curators in this task, we recently added a text annotator tool to the Phenoscape Knowledgebase that tags selected text passages copied in from a source with matched terms from anatomy (Uberon), taxon (VTO), and quality (PATO) ontologies. Viewing the annotated results, with color-coded text, has aided curators in the process of applying large, complex ontologies to equally complex text.

Filed under: Uncategorized
Dec 302015

Biosphere 2, the site of the final Phenotype RCN Summit meeting (February 2016). Photo (CC BY-NC 2.0) by pinkgranite. See original at

The Fifth Annual Summit of the Phenotype Ontology Research Coordination Network will be held at the University of Arizona’s Biosphere 2, about 40 miles north of Tucson, AZ, from February 26-28, 2016 (Friday through Sunday noon).

The theme of this meeting will be ‘Complex data integration with phenotypes’ with a focus on the integration of phenotype data with other data sets. We will summarize where our phenotype community is at with respect to integration with other data types, and we will highlight active projects. We will be looking to the future — what projects should be priorities for the future? Joining us this year will be folks from the newly funded ‘FuturePhy’ (, who are interested in how to integrate multiple data types, including phenotype, with phylogenetic trees.

We estimate that the costs for this meeting (transportation to meeting from airport, lodging, food) will be approximately $500, though we will be able to cover expenses for a small number of participants, particularly students and postdocs who have specific interests in using phenotypic data associated with environment in their research. Please contact one of us if you are interested in attending. It should be agreat meeting!

Paula Mabee;
Eva Huala;
Andy Deans;
Suzanna Lewis;

The Phenotype Ontology RCN ( was funded by the U.S. NSF to establish a network of scientists who are interested incomparing phenotypes across species and in developing the tools and methods needed to enable comparisons. In contrast to the many well-established efforts in the molecular community, the representation of phenotypic traits using ontologies is in its infancy. Phenotype ontologies, however, have the potential to integrate these data across all levels of the biological hierarchy and to the environment. This RCN is building a community that, because of its expertise, fosters communications across disciplines to enable co-development of interoperable community standards and best practices for phenotype.

 Posted by on December 30, 2015 at 1:50 am
Dec 212015

The following post is from Peter Midford. – Andy Deans

As you may recall, at a Spring 2013 meeting of the Phenotype RCN in Durham, NC, the Behavior Breakout group discussed the existence of multiple behavioral ontologies, including the gaps in existing ontologies (such as the Neuro Behavior Ontology, or NBO) that preclude their widespread use in behavioral ecology and other sub-disciplines in animal behavior. The group felt it could be possible to merge two existing behavioral ontologies – the NBO, developed to serve studies of animal models of human behavioral dysfunction, and the Animal Behavior Ontology or ABO, developed to serve the field of comparative animal behavior, including behavioral ecology and other sub-disciplines. If successful, the merger would facilitate the broader integration of behavioral studies: applied with basic, model organism with comparative investigations, mechanistic with evolutionary, and human with non-human animal questions. At the same time, it would also need to continue to serve the specialized needs of subfields.

In late summer 2014, a small group of animal behaviorists who were present at the 2013 meeting in Durham (Anne Clark, Sue Margulis, Peter Midford, Cynthia Parr) received NSF funding to hold two workshops to accomplish these goals.

Our first workshop, held August 2014 at Princeton University, convened over a dozen animal behaviorists with a broad range of expertise in comparative behavior to develop specific recommendations on how to integrate the basic terms and concepts of the two ontologies. Key outcomes included a list of proposed changes in parent-child relations in the NBO to emphasize function, and ABO term definition improvements that together could serve as the basis of integrating the two ontologies.

Our second workshop, supported in part by additional funding from the Phenotype RCN, was held at the Smithsonian’s National Museum of Natural History, Washington, DC, on October 24-25, 2015. Its specific goal was to start the process of merging the ABO and the NBO based on the first workshop’s recommendations. Attendees in addition to the four organizers, were our local host Katja Schultz (Encyclopedia of Life), Elissa Chesler (The Jackson Laboratory), George Gkoutos (NBO developer, University of Birmingham), David Osumi-Sutherland (European Bioinformatics Institute, Virtual Fly Brain), Melissa Haendel (Oregon Health and Science University), and Reid Rumelt (Cornell University undergraduate working with Macaulay Library and Encyclopedia of Life).

The workshop began with presentations about the histories of NBO and ABO. NBO had its roots in a phenotype vocabulary supporting the EUMORPHIA project (see and Behavior terms were initially included in the Gene Ontology, but also maps to phenotype ontologies, such as the Mammalian Phenotype ontology (MP) and Human Phenotype Ontology so as enable the integration of data. The Neuro Behavior Ontology was created to concentrate effort specifically on behavior.


ABO was one of the first accomplishments of the EthoSource project1, begun with an NSF-sponsored workshop in 2000 with the goal of developing integrated online resources for the discipline of Animal Behavior. Two NSF- sponsored Ontology Workshops followed in 2004-2005, at which an international group of animal behaviorists developed a basic metadata standard for the discipline, the ABO. The primary use of the ABO subsequent to 2005 was indexing an online ethogram repository,

In our second blog post, we will summarize the progress we made in the October workshop, and outline our next steps.

1Martins, E. P. 2004. EthoSource: Storing, Sharing, and Combining Behavioral Data. BioScience 54 (10): 886. doi:10.1641/0006-3568(2004)054[0886:ESSACB]2.0.CO;2

 Posted by on December 21, 2015 at 3:49 pm
Dec 182015

The following post is from Anne Thessen, who originally published this news on her blog, The Data Detektiv. – Andy Deans

One of the fundamental goals of biology is understanding the interactions of environment and phenotype, but this is a surprisingly difficult topic to study – not because of the concepts, but because of the data. Observations about environment and phenotype occur in separate data sets and the terms used are far too idiosyncratic for automated integration. Several biological domains, including conservation and phylogenetics could be advanced if these two data types could be easily merged on a large scale.

I led a recent paper, published in PeerJ, which suggests that the use of ontologies to standardize and link data about phenotypes and environments can enable scientific breakthroughs by increasing the scale and flexibility of research. This paper was a product of a workshop facilitated by the Phenotype RCN and supported by the National Science Foundation. My co-authors and I give several domain-specific use cases describing how an ontology can help advance science in four biological sciences. We then discuss the challenges to be addressed, present some proof-of-concept analyses, and discuss existing ontologies. The summary contains three suggestions for increasing interoperability between phenotype and environment data.

graphical illustration of the paper described in this blog

Graphical abstract for Thessen et al. (2015) DOI: 10.7717/peerj.1470. Click to enlarge.

We hope this paper provides you with an overview of the landscape of ontologies available for integrating environmental data, and inspires you to use them in relation to your own data. For more information about ontologies and semantics, a good first read is Semantic Web for the Working Ontologist by Dean Allemang and Jim Hendler.

 Posted by on December 18, 2015 at 2:27 am
Jul 272015
prickly plant leaf

Succulent plant with interesting adaptive phenotypes. Photo taken at the Rancho Santa Ana Botanic Garden (RSABG) by Manicosity (CC BY-ND 2.0). Click for original.

Supported by a Phenotype RCN collaboration grant, Grant Godden and Pier Luigi Buttigieg met during May 2015 at the Rancho Santa Ana Botanic Garden (RSABG) in Claremont, CA, with the aim of enhancing the ontological representation of plant environments. Grant and Pier processed label data from more than one million plant specimen records hosted by iDigBio, using a combination of natural language processing and text-mining techniques to identify well-represented terms and phrases in “habitat” descriptions. Their interactions with RSABG collections staff, whose active work with specimen digitization and insights into the creation of records that populate repositories like iDigBio, greatly enhanced the project and helped create a workable corpus. The preliminary results of the analyses were immediately informative, revealing gaps in the current coverage of the Environment Ontology (ENVO; Buttigieg et al., 2013).

Further work is planned to refine their computational pipeline and corpus, and to extend ENVO’s coverage of environments which the botanical community frequently sample. A brief publication reporting the process, findings, and results is in preparation.

GG is affiliated with the Rancho Santa Ana Botanic Garden, Claremont, CA, USA. PLB is affiliated with the Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany.

 Posted by on July 27, 2015 at 5:33 pm
Jun 102015

Visualizing one or more trees/taxonomies with non-trivial number of characters and taxa is a challenge a number of projects is facing. The ETC project organized a workshop with information visualization experts, data providers (trees and characters), and end users to tackle the challenge together.
The meeting was organized by Hong Cui and hosted by Bertram Ludäscher in the National Center for Supercomputing Applications (NCSA), Urbana, IL, in May 11-13. Phenotype RCN participants Matt Yoder, Nico Franz and Martín Ramírez attended the meeting and posed vis challenges. Much of the workshop was devoted to brainstorm on the challenge of representing a large dataset together with some kind of mapping on a tree, and often on two trees simultaneously. This is a familiar challenge for anatomy ontologists, who are trying to represent the interaction of phylogenetic trees, matrices and ontologies:

Right, the level of anatomical data available for different parts of the fin and limb can be visualized for taxa along the fin to limb transition (figure from Dececchi et al. in press 2015, Systematic Biology, doi: 10.1093/sysbio/syv031). Left, a phylogeny of spiders colored according to anatomical complexity, derived from the ontology (figure from Ramírez & Michalik 2014, doi: 10.1111/cla.12075).

Right, the level of anatomical data available for different parts of the fin and limb can be visualized for taxa along the fin to limb transition (figure from Dececchi et al. in press 2015, Systematic Biology, doi: 10.1093/sysbio/syv031). Left, a phylogeny of spiders colored according to anatomical complexity, derived from the ontology (figure from Ramírez & Michalik 2014, doi: 10.1111/cla.12075).

The beautiful and clever examples presented by the vis experts were inspiring. How these gorgeous examples can help us represent or complex data in intuitive visualizations? Filters, sort controls, heat maps, zoom panes, collapsing, expanding, and more tools – all made in us two effects: Make some of our challenges look feasible, and refine our vague ideas into more precise challenges.
Hierarchical Circular Layouts, or HCL (Dang, Murray, and Forbes 2015), uses circular layouts on a hierarchical structure.

Hierarchical Circular Layouts, or HCL (Dang, Murray, and Forbes 2015), uses circular layouts on a hierarchical structure.

PathwayMatrix: Visualizing Binary Relationships between Proteins in Biological Pathways (Dang, Murray, and Forbes, 2015). PathwayMatrix can be used not only for biological pathway visualization, but also for character and taxon data.  See:

PathwayMatrix: Visualizing Binary Relationships between Proteins in Biological Pathways (Dang, Murray, and Forbes, 2015). PathwayMatrix can be used not only for biological pathway visualization, but also for character and taxon data. See:

The ETC project will implement a few promising techniques as part of ETC toolkit to invite comments and suggestions from broader communities. Stay tuned, and crunch your data into nice visualizations!
(post by Martin Ramírez)