This Dashboard highlights the top institutions and labs throughout the world using the Nanostring, Fluidigm, and Wafergen microfluidic platforms.
Microfluidics Trends: 2005 – 2015
By applying various microfluidics engineering approaches, several technology companies are paving the way for researchers to study minute amounts of sample including single cells and molecules.
These approaches are valuable in that they mitigate the dilutive impact heterogeneous samples can have on when attempting to identify novel biomarkers, or profile samples for a specific biomarker of interest.
In this Dashboard, we look at three of the early leaders in microfluidic-based technology companies that provide both platforms and reagents for key applications like single cell analysis: Wafergen, Nanostring, and Fluidigm.
Inside this Microfluidics Market Trends Dashboard
This Market Trends Dashboard summarizes the growth in adoption and use of several popular microfluidics platforms used in targeted analysis and single cell studies (Wafergen, Nanostring, and Fluidigm).
Inside it you’ll find:
- The relative usage of these methods as measured in total volume of publication mentions
- The total volume of mentions over time
- The growth rate trending for the methods
- Regional segmentation: total mention volume and growth rates broken down for reach region, country, and even by state in the US
Add Some Life and Sciences into your CRM
If you’re like most life sciences marketers, you’re now swimming (often upstream) in data. It started innocently enough about a decade ago with web analytics data and email campaign metrics, then got fancier with the more progressive profiling capabilities of some marketing automation platforms.
Today, even the more advanced marketing teams acquire data with a series of yes/no answers to forms, web activities, and campaign engagement.
These are all great things to . . .View full post
Research Profile Navigation
This brief video provides an introduction to our Research Profile Dashboards and highlights their basic functionality . . .View full post
Market Trends Dashboard Navigation
This video reviews the basics of navigating our Market Trends Dashboards . . .View full post
Navigating Dashboard Maps
The following screencast shows how to navigate the interactive maps within our Dashboards . . .View full post
How do your projections differ from Google Scholar, Highwire, and PubMed and PubMed Central
Citalytics data estimates will not always resemble what you’ll find in other databases. This is related to a number of factors and how other databases display information.
Let’s take a look at some popular tools out there.
Google Scholar has access to many scholarly sources which is great. It also allows full-text searching which is also nice.
Where things start to get complicated is that Google Scholar pulls in information and indexes it by relevance, just like they do search results for web browsing. Generally, it will display the first 1,000 records for each search regardless of how many exist. This is because, if you’re looking for scholarly information, Google will likely be able to point you in the right direction within the first 1,000 records.
What it doesn’t allow you to see is how specific the remaining results are. So if Google Scholar says there are 10,000 results for your query and the show you the best 1,000, you really have no way of knowing how specific the remaining 9,000 results and how accurate the estimate of 10,000 records really was.
Highwire is a platform for publishers that allow them to disseminate their publications without the investmnet and carrying costs in IT infrastructure. Because of this, Highwire’s results are generally limited to their publishing partners resulting slightly lower numbers of mentions.
That said, Highwire also houses results for posters and meeting summaries etc., so occasionally results could be higher than what is available in peer-review journals, particularly in the early stages of a technology, method, or brand.
PubMed has a lot going for it in terms of its recency and validity as the source for peer-reviewed publications. What it doesn’t have going for it though, it full-text search. When you do a search in PubMed, it is searching the Title, Abstract, and Keyword-type fields, rather than the full text.
This works well in general as people looking for specific research topics will likely find what they’re looking for in the abstract and/or title. It does reduce the overall data that you’ll see, however, so the number of results will be significantly lower.
PubMed Central is a large database that houses the full-text from many journals. This provides advantages in that a text search of PubMed Central will query the entire paper and generally display more hits.
The only downside of PubMed Central is that there is a delay from when the paper publishes vs. when it appears in the database.
This may not be a big deal if you’re looking for historical information, but it could be a major negative if you’re looking for recent data.
Where do you get your data?
Our proprietary algorithms monitor numerous public databases that house millions of publications from nearly 20,000 publishers. Our custom workflow has been refined over nearly 5 years of development and allows us to obtain different data “pieces” from a variety of databases that enable us to monitor scientific journals for key trends and research activity.
Don’t be shy. If you have any questions about our data or services, please don’t hestitate to drop us a line at: email@example.com
What's a Research Profile Dashboard?
Our Research Profiles capture key authors working in a given research area. We produce these my tracking all citations, then using corresponding authors* to produce author profiles that roll up into top institutions.
They’re a very useful tool to identify key institutions by volume of research activity, but also understand how many authors are contributing at an institution and how much.
*By using corresponding authors, we are capturing a large sample of authored papers, but of course, not all. We use corresponding authors because they generally coincide with senior PI level individuals at Life Sciences labs. This is not always the case in other fields (i.e. Physics), but does work well in biological sciences.
What is a Market Trends Dashboard?
Our Market Trends data captures the trending of key applications, methods, and/or product brands in peer-review literature. They provide a high level look at how widely different methods or brands are being utilized in labs around the world. These datasets can help you understand market opportunities, usage share, or product uptake.