Archive for the ‘Author’ Category

Protect Yourself from Zombie Papers

Posted on April 25th, 2016 in Anita Bandrowski, Data Spotlight, NIFarious Ideas | No Comments »

Another fun flier to post around the department.

Zombification of papers: the inability to use or validate information in the paper.
How can we stop this terrible plague on the scientific literature? – RRIDs help get the Key biological reagents identified and authenticated.

Feel free to print this fun flier and post it on your office door!

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RRID: Improve your Impact Factor!

Posted on April 25th, 2016 in Anita Bandrowski, News & Events, NIFarious Ideas | No Comments »

Please feel free to take this fun flier and post it around your lab to help your lab-mates to remember how to get an RRID into your next methods section or grant application.

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Reproducibility in the Recipes of Science

Posted on March 31st, 2016 in Anita Bandrowski, Essays, Interoperability, News & Events | No Comments »

Hello SciCrunch/NIF Community! Please read below for Dr. Bandrowski’s post on “Reproducibility in the Recipes of Science”

Reproducibility in the Recipes of Science

Reproducibility in science is a very difficult question, with much that has been said about it from industry, government and researchers themselves, for a good summary please see [Nature Special]( on reproducibility.

Many more things can and will be said about this complex issue, but I wanted to ask a different question: do we not already have a good exemplar of reproducibility when we look at our favorite recipe sites? There are list of ingredients, pictures of the finished product, and of course plenty of detailed instructions. There are even places for novice cooks to tell the recipe owner “hey this is hard to reproduce” or “it does not work with Indian saffron”.

Why doesn’t the **methods** section of our papers not look like that?

I would like to introduce the members of the Society for Neuroscience to an initiative that has been trying to move the methods to look a little more like your favorite recipe site, by asking authors to do a little more thorough job when listing their key ingredients, such as antibodies.

It has been going on for a couple of years years as an agreement between several of the key journals in neuroscience, which ask authors to provide an RRID, or a unique identifier for key biological reagents in their methods sections. Currently these RRIDs are generated for antibodies, organisms and software tools.

We are very pleased that [eNeuro]( has recently joined the charge as has [Neuron](, so you may be seeing some of these RRIDs in the papers that you read.

However, we know that many journals will allow authors to add the RRIDs to their papers even if the journals are not officially pushing authors themselves, so we hope that you will join the charge with your next paper. Please go to []( and search for your key biological resources, open the “cite this” box and copy the citation into your methods. This way, tracking down the ingredients used in any paper becomes much easier and that is of course the first step in experimental reproducibility.

Eating my own Dog Food!

Posted on July 4th, 2015 in Anita Bandrowski, Curation, Interoperability, News & Events | No Comments »

While not all of you have been fortunate enough to attend the first Beyond the PDF meeting, I will say this; it was eye opening for this scientist. To me, the most memorable statement from the meeting was when Geoffrey Bilder argued from the back of the room that we should all Eat Our Own Dog Food! What he meant was that anyone building tools should actually use them or proclaiming any broad “thou shalt-s” should himself live up to the particular proclamation.

Easier said than done, Geoffrey!

In the years since this historic meeting, these statements have been eating away at my psyche.

I lead the Resource Identification Initiative, a project to add unique identifiers to all papers that use: antibodies, model organisms, software tools or databases. Basically I am telling authors to do “my bidding” and make their papers better to search and give academic credit to developers of software tools like R or ImageJ. I am asking these authors to help others selflessly and do something different than they have done before.

When submitting a paper to Frontiers in NeuroInformatics, as a middle author at the very beginning of the RII project, I felt very reluctant to add RRIDs to the paper. Who was I to suggest such a thing? I waited for the editor to remind us to add the identifers, I waited and no question came. Before final submission, I overcame my very uncharacteristic muteness and asked my collaborators to add the RRIDs to a table where I felt they were appropriate. It turned out that my colleagues did not object and the journal editor, also didn’t say anything about including them. His journal was not yet on board, something that has been remedied since.

Why did I feel so strongly that I should not include an identifier for tools while telling others to do it?
What was I afraid of?
Change is hard!

I am really not sure now what I was so afraid of because after overcoming this initial scientific recalcitrance I simply put RRIDs in the next paper without a second thought and continued to put them in since.

So as I was drafting this blog, a colleague asked me to contribute to a table in her paper, I will be one of those middle authors (huge paper with tons of authors), but this time as with my own papers I have asked her to include the RRIDs without being afraid; it took me about 8 minutes to pull all relevant RRIDs from and the paper was just submitted. I do not care if the journal is participating in the initiative officially or not.

I guess that what I have learned from all of this, is that once you accept change it becomes the new normal and RRIDs are a great new normal. Thanks Geoffrey for nagging me, I am very glad to say that I have Eaten My Own Dog Food!

NIH Plan for Increasing Access to Scientific Publications and Digital Scientific Data

Posted on March 4th, 2015 in Anita Bandrowski, Interoperability, News & Events | No Comments »

The NIH put out a plan to increase access to scientific data.

What do they really mean and what does this mean to researchers?

Researchers have been asked to provide PubMed Central PMC identifiers in grant applications and this single requirement has pushed authors to submit their papers to PMC and many journals do this as a matter of fact leading to a large corpus of publications that are fully searchable texts. I think that researchers are now familiar with this process and see the benefit, as I do when I am at home and need to look up a piece of information from my old paper that a publisher tries to charge me $36 to find.

What happens to data and what is meant by data?
Will authors need to submit all of their supplementary data files to PMC?

Perhaps not, some wording in the document from the NIH shows that they know that data is not homogeneous. They recognize that they can’t handle the diversity in a good way without working with existing repositories.

They point out that data should be FAIR:
This is known as the FAIR standard.

They also state:
“A strategy for leveraging existing archives, where appropriate, and fostering public- private partnerships with scientific journals relevant to the agency’s research; Encourage public-private collaboration; Encourage public-private collaboration to … otherwise assist with implementation of the agency plan; Ensure that publications and metadata are stored in an archival solution that… uses standards, widely available and, to the extent possible, nonproprietary archival formats for text and associated content (e.g., images, video, supporting data).”

So will there be a set of repositories that are “approved” community standards? Will the NIH have a box for grantees to put in their community repository IDs?
Seems like a good direction!

For now, NIF has a very large list of repositories that will house your data.
Try this registry search.
There are over 1000 that respond to the query, but which one or which ones can you use?
It does not seem that the NIH is willing to be proscriptive, so it will be left to individual communities to rally around repositories that best serve them.
For now, NIF just aggregates the information around these and attempts to make them findable (the F in FAIR).

Integrated Annotation just added the 7-million-th record

Posted on February 27th, 2015 in Anita Bandrowski, Data Spotlight, News & Events | No Comments »

Yes we do have annotations!

What can we do with these annotations?

* When you are reading a paper, would you like to know if the data you are looking at has been stored somewhere?

* Would you like to know if someone figured out what antibody the authors used?

* What about the mouse described in the paper, is there additional information in MGI?

The integrated annotation view is an aggregate of any database included in NIF that contains the PubMed Identifier.

In over 50 databases there are citations containing PubMed Identifiers, a reference for a particular data record. While each database is different, there are some themes. Records may include reagents used in the paper like AddGene plasmids, data that is stored somewhere like ModelDB computational models, or they may include a set of values that were extracted from the paper like BioNumbers.

Through a software tool called the LinkOut Broker, we submit these data to PubMed (unless the database does this already), an annotation that says this paper is referenced in a particular database. However, these citations are not searchable in PubMed and so we have made the integrated annotation view to allow NIF users to search these same annotations.

However, we know that people read papers in many places, pdf readers and on line so we have started working with several groups including a team at Science Direct to push the data into the places where the readers are. We are proud to work with the Elsevier Antibody App team, who created an application visible in Science Direct in all Elsevier papers that have an antibody annotated in the

An example paper from Experimental Neurology can be viewed here

The NIA Butler-Williams Scholars Program

Posted on February 27th, 2015 in Anita Bandrowski, News & Events | No Comments »

The NIA Butler-Williams Scholars Program (formerly Summer Institute on Aging Research) is accepting applications for an intensive introduction to aging research. This program for investigators that are new to aging research is focused on the breadth of research supported by the National Institute on Aging, including basic biology, neuroscience, behavioral and social research, geriatrics and clinical gerontology. As an offering through the NIA Office of Special Populations, program content will include a focus on health disparities, research methodologies, and funding opportunities. The Butler-Williams Scholars Program (B-W Scholars) is one of the premier, short-term training opportunities for new investigators. New researchers are defined as those who have recently received the M.D., Ph.D. or other doctoral level degree. The B-W Scholars Program provides participants with unparalleled access to NIA and NIH staff in an informal setting.

The 2015 B-W Scholars Program will be held July 27-31, 2015 in Bethesda, Maryland. Support in most cases is available for travel and living expenses.  The B-W Scholars Program is sponsored by NIA with support from the National Hartford Centers of Gerontological Nursing Excellence.

***Applications are due Friday, March 27, 2015***

Researchers with an interest in health disparities research are encouraged to apply. Applicants from diverse backgrounds, including individuals from underrepresented racial and ethnic groups, individuals with disabilities and women are always encouraged to apply for NIH support. Applicants must be U.S. citizens, non-citizen nationals, or permanent residents.
Please view more information on the NIA web site:

For more information, please contact:
Ms. Andrea Griffin-Mann
Office of Special Populations
National Institute on Aging
National Institutes of Health

Did you know? The IMPC maintains a large list of predicted mouse gene phenotypes

Posted on February 16th, 2015 in Anita Bandrowski, Data Spotlight, News & Events | No Comments »

The Monarch project ( with the NIF project have brought in many sources that are now available from NIF or many of the SciCrunch portals that contain a wealth of phenotype information.

The International Mouse Phenotyping Consortium is one of these sources and the creates, curates, and maintains targeted knockout mutations in embryonic stem cells for 20,000 known and predicted mouse genes. These phenotypes are available through several views showing the variant phenotypes.

What can be learned from phenotype data? Phenotype is a superset of disease, so this data can be instrumental in figuring out if a better model for the disease you are studying exists and what are the associated traits to each organism. A worm researcher may not be aware that a fly mutation expresses the same phenotype, but perhaps does so as a result of a different genotypes / knockouts.


Check out other sources of phenotype data also available:

WormBase provides anatomical and genetic information of C. elegans and related research nematodes. This Worm:VariantPhenotypes view curates the relationship between an allele and a phenotype, where the allele can be a genetic or RNAi-induced change. 100.00% (543,874 Results)

Online Mendelian Inheritance in Man (OMIM) curates human genetic diseases from the literature. The OMIM:VariantPhenotype view describes the curated relationships between genes, allelic variants (if available), and diseases/traits. 100.00% (28,706 Results)

WormBase provides anatomical and genetic information of C. elegans and related research nematodes. The GeneExprLoc view shows the localization of gene expression in C. elegans anatomy. 100.00% (72,346 Results)

OMIM is a human curated authoritative source of information about disease to gene connections. The DiseaseGeneAssociation view is organized by the OMIM phenotype/disease identifiers, and lists all genes and text annotated to a given disease or phenotype. more about OMIM      100.00% (4,809 Results)

HPO annotations provide annotations of human phenotypes and diseases. This phenotype to gene view is the associations between a phenotype and it’s putative causative gene based on the link between a gene and it’s known involvement in a disease. 100.00% (284,441 Results)

The Mouse Phenome Database is a project at the Jackson Laboratory, which characterizes mouse studies based on the types of measurements that are made in each study. This MeasurementDefinitions view shows the curated mappings of the assay measurements to the relevant phenotype, trait, and anatomy terms at are measured. 100.00% (14,765 Results)

The HPO group provides annotations of phenotypes of human diseases, linked to OMIM, Orphanet, and DECIPHER.    100.00% (116,600 Results)

Online Mendelian Inheritance in Animals (OMIA) is a data set describing phenotype relationships with individual breeds and genes. This BreedPhenotypes view curates species and breed-specific-phenotype relationships for non-model organisms. 100.00% (15,516 Results)

Animal Quantitative Trait Loci Database collects and provides publicly available trait mapping data, i.e. QTL (phenotype/expression, eQTL), candidate gene and association data (GWAS), and copy number variations (CNV) mapped to livestock animal genomes to facilitate locating and comparing discoveries within and between species. Additional information regarding QTL data can be found at the Animal QTL Database FAQ.   100.00% (28,751 Results)

The ZFIN Genotype-Phenotype View  contains Genotype-to-Phenotype mappings in ZFIN, with experimental-environmental context. This Genotype-Phenotype view is a combination of intrinsic (organismal) and extrinsic (experimental/morphant) genotypes, in the context of environmental conditions. The effective genotypes are extracted and built from ZFIN genotype-phenotype data following the GENO genotype ontology model as developed by the Monarch Initiative. 100.00% (85,118 Results)

FlyBase is a database of genetic and molecular data for D. melanogaster and other Drosophila species. Flybase:Phenotypes are the curated links for phenotypes of the flies of a specified genotype, in a specified environment, attributed to a publication. 100.00% (275,697 Results)

The International Mouse Phenotyping Consortium creates, curates, and maintains targeted knockout mutations in embryonic stem cells for 20,000 known and predicted mouse genes. The IMPC:MousePhenotypes view reports on the genotypes and associated phenotypes collected from a broad based primary phenotyping pipeline in all the major adult organ systems. All phenotype calls are found to be significant with a p-value < 1 x 10-4. 100.00% (7,156 Results)

Mouse Genome Informatics offered by Jackson Laboratory includes information on integrated genetic, genomic, phenotypic, and biological data of the laboratory Mouse. The MGI:Phenotypes view presents the curated relationships between genotypes and phenotypes. 100.00% (275,856 Results)

The NHGRI Elements of Morphology: Human Malformation Terminology is being developed by a group of international clinicians working in the field of dysmorphology to standardize terms used to describe human morphology, thereby increasing the utility of descriptions of human phenotype and facilitating reliable comparisons of findings among patients. 100.00% (400 Results)

The Mouse Phenome Database is a project at The Jackson Laboratory which collects and curates mouse strain survey data for behavior, physiology, and anatomy. Data are available for inbred and recombinant inbred strains, chromosome substitution strains, other classical panels, Collaborative Cross (CC) lines and Diversity Outbred (DO) populations. 100.00% (235 Results)

The ClinVar aggregates information about sequence variation and its relationship to human health. The ClinVar:VariantPhenotypes view provides information on sequence alterations present in genes and the resulting phenotypes. For records listing more than one variation, data is presented with the assumption that the individual sequence alterations are in cis. 100.00% (458,639 Results)

The Mouse Phenome Database is a project at The Jackson Laboratory which collects and curates mouse strain survey data for behavior, physiology, and anatomy. Data are available for inbred and recombinant inbred strains, chromosome substitution strains, other classical panels, Collaborative Cross (CC) lines and Diversity Outbred (DO) populations. The MPD:StrainPhenotypes view computes the extreme outlier phenotypes (>2 s.d.) as compared to the overall mean for each assay, and maps the quantitative measurements to their qualitative phenotype. (The strains measured for each assay varies, and therefore the means computed may be drawn from collections of different strains.) 100.00% (8,605 Results)

The International Mouse Phenotyping Consortium creates, curates, and maintains targeted knockout mutations in embryonic stem cells for 20,000 known and predicted mouse genes. The IMPC:KnockoutPhenotypes view reports on the phenotypes collected from a broad based primary phenotyping pipeline in all the major adult organ systems. 100.00% (7,156 Results)

Webinar from BioCaddie (aka DDI): Jeff Grethe presents NIF

Posted on February 9th, 2015 in Anita Bandrowski, News & Events, Webinar Announcement | No Comments »

Cooperative and collaborative data and resource discovery platforms for scientific communities – The Neuroscience Information Framework (NIF) and SciCrunch


Date: Thursday, February 12, 2015
Time: 10:00 AM – 11:00 AM (PST); 1:00 PM – 2:00 PM (EST)



Jeffrey S. Grethe, Ph.D.
Associate Director, Center for Research in Biological Systems
University of California, San Diego


Data and information on research resources are everywhere, in numerous repositories and download sites, and more floods in every day. What’s a researcher to do? In order to be able to use shared data, the first fundamental rule is that you have to be able to find it. We have search engines like Google for web documents, PubMed and Google Scholar for articles, NCBI for selected genomics resources. The Neuroscience Information Framework (NIF; was instantiated in 2006 in response to a Broad Agency Announcement from the NIH Blueprint for Neuroscience Research citing an overwhelming need for an ”information framework for identifying, locating, and characterizing neuroscience information”. NIF was tasked with surveying the neuroscience resource landscape and developing a resource description framework and search strategy for locating, accessing and utilizing research resources, defined here as data, databases, tools, materials, literature, networks, terminologies, or information that can accelerate the pace of neuroscience research and discovery. NIF adds value to these existing biomedical resources by increasing their discoverability, accessibility, visibility, utility and interoperability, regardless of their current design or capabilities and without the need for extensive redesign of their components or information models. Unlike more general search engines, NIF provides deeper access to a more focused set of resources that are relevant to neuroscience, provides search strategies tailored to neuroscience, and also provides access to content that is traditionally “hidden” from web search engines. To accomplish this, NIF has deployed an infrastructure allowing a wide variety of resources to be searched and discovered at multiple levels of integration, from superficial discovery based on a limited description of the resource (NIF Registry), to deep content query (NIF Data Federation). It is currently one of the largest sources of biomedical information on the web, currently searching over 13,000 research resources in its Registry, and the contents of 250+ data resources comprising more than 800 million records in its Data Federation.

Building on the NIF infrastructure, SciCrunch was designed to help communities of researchers create their own portals to provide access to resources, databases and tools of relevance to their research areas. A data portal that searches across hundreds of databases can be created in minutes. Communities can choose from our existing SciCrunch data sources and also add their own. SciCrunch was designed to break down the traditional types of portal silos created by different communities, so that communities can take advantage of work done by others and share their expertise as well. SciCrunch currently supports a diverse collection of communities in addition to NIF, each with their own data needs: CINERGI – focuses on constructing a community inventory and knowledge base on geoscience information resources; NIDDK Information Network (dkNET) – serves the needs of basic and clinical investigators by providing seamless access to large pools of data relevant to the mission of The National Institute of Diabetes, Digestive and Kidney Disease (NIDDK); Research Identification Initiative (RII) – aims to promote research resource identification, discovery, and reuse.


Dr. Jeffrey S. Grethe, Ph.D. is a Principal Investigator (MPI) for the Neuroscience Information Framework (NIF; and the NIDDK Information Network (dkNET; in the Center for Research in Biological Systems (CRBS; at the University of California, San Diego. Following a B.S. in Applied Mathematics from the University of California, Irvine, he received a doctorate in neurosciences with a focus on neuroinformatics and computational modeling from the University of Southern California. Throughout his career, he has been involved in enabling collaborative research, data sharing and discovery through the application of advanced informatics approaches. This started at USC with his involvement in the Human Brain Project and continues today with his work on NIF, dkNET and with standards bodies such as the International Neuroinformatics Coordinating Facility.

Details on how to join Webinar:

*Must use Web and Audio*

Please include name and company when joining meeting. Web: (Join meeting with Access Code 2201876)
Audio: 1-866-740-1260 (Access Code 2201876)
Click here to test your computer’s compatibility before the meeting.

This webinar is open to all.
More information about this webinar, future webinars and events can be found at:

The Journal of Comparative Neurology Reaches 100 RRID papers!

Posted on February 5th, 2015 in Anita Bandrowski, News & Events | No Comments »

Have you ever wondered how can you find validated antibodies?
Have you ever wondered where most of our literature mentions come from in the

Well, wonder no more. Neuroscience Information Framework and more specifically the has been working closely with the Journal of Comparative Neurology (Bandrowski et al., JCN 2013) to enhance the already high standards of antibody identification of JCN papers.

In the Research Resource Identification initiative we have just crossed a major mile stone, the 100 papers in a single journal and the journal that takes this is not surprisingly JCN. Most of these papers identify the antibodies they contain with unique identifiers in the following format RRID:AB_2298772, which can be searched for in google scholar or PubMed.

The growing number of papers and the growing number of journals (42 and counting) suggests that this standard fills a need in the community.

If you wish to join the initiative as an author, just visit the SciCruch resource portal and search for your antibodies, a convenient “cite this” button will give you the text to use in your methods section.
If you wish to join as an editor, we have draft letters to authors and author guidelines that you can use at Force11.