Mendeley's top time-saver tips for early career researchers.

So you’ve slaved away all year long, passing up pool party and barbecue invitations to feed the needs of the research beast, and you’ve finally got something to show for it. The next question is how do you get it published, where, and what do you do after that so it doesn’t end up with two readers, one of which is your mom? We won’t presume to tell you where, but we do have a few tips for things to consider, which you may have missed because you were slaving away at the bench or in the library like a good student and not reading up on all the cool stuff that’s happened this summer in the exciting world of academic publishing. So here’s our summary of the new (and we presume you’ve already heard the old from your PI).Read More »

Yale iGEM Team Uses Mendeley to Make Collaboration Easier

Yale Team


A while back, we heard from a group of students at Yale University working for a really exciting project called iGEM. They wanted to use Mendeley so they could collaborate better in their research, and we were more than happy to help out. We also thought it’d be nice to share their experience and insights with the Mendeley community:

We’re the Yale iGEM team, a team of eight undergraduates who research synthetic biology and participate in the annual iGEM (international genetically engineered machines) competition.

From glow-in-the-dark bacteria to fuel-producing cyanobacteria, synthetic biology has a wide variety of applications that can be used to better our world. Each year, the Yale iGEM team comes together to produce a project that uses engineered biology to solve industrial, medical and environmental problems.

Synthetic biology is an emerging subset of science that focuses not only on the study of natural biological systems, but the alteration and design of novel systems. This year, our team is aiming to engineer a common strain of bacteria so that it produces polylactic acid (PLA), a biopolymer and plastic substitute that is cheaper, cleaner to make, and biodegradable.

Mendeley has been really useful in helping with organizing all the background literature and research we have investigated in order to achieve our team’s goals. It’s a great place to store, share and comment on the research that serves as our project’s foundation.

Our university software library offers a few options for reference managers, but Mendeley is more useful to us because it enables a collaborative workspace that doesn’t require us all to be in the same room. In our team, we might have three full-time student researchers in our summer lab while the rest of our researchers may be pursuing other opportunities around the world, so we can’t always meet face-to-face.

Mendeley supported us with an upgraded team package and we have found the ease of adding in members, importing and organizing documents to be highly useful. In addition, the team found that Mendeley combined e-mail, cloud drive and reference management in a very elegant and intuitive way.

We’re grateful for the support and now are really looking forward to the outcomes of our research. We hope to have results by the iGEM World Competition in November 2013, and we’ll post them when they become available!



Mendeley Mini-Conference on Recommender Systems

Mendeley Recommender Workshop

Last week, Mendeley hosted an all-day mini-conference on Academic-Industrial Collaborations for Recommender Systems.  As we’re fast running out of space in our London office, we rented a nearby venue called Headrooms.  With friendly staff looking after everyone’s needs and great start-up décor, we’ll definitely be coming back for future Mendeley event.  In the morning and early afternoon we were treated to seven talks from a variety of speakers who shared their experiences of academic-industrial collaborations and recommender systems.  We finished the afternoon by splitting into smaller groups to discuss the challenges involved in making such collaborations a success and sharing useful advice with one another.  The day then finished, as all good days do, with a quick trip to the funkily named Giant Robot, to taste some of their excellent cocktails. Our Chief Data Scientist Kris Jack, who masterminded this great event, shares some of the day’s highlights:


Seven presentations were delivered by our eight speakers, one of them being an entertaining double act.  We tried to film as much of the event as we could so we could share them with you, so click on the links below to watch the presentations!

First off, Jagadeesh Gorla began with a presentation entitled A Bi-directional Unified Model.  Jagadeesh talked about the results presented in his www2013 paper on group recommendations via Information Matching, a new probabilistic model based on ideas from the field of Information Retrieval, which learns probabilities expressing the match between arbitrary user and item features: this makes it both flexible and powerful.  He is currently working on developing an online implementation for deployment in an online gaming platform.

Our double act, Nikos Manouselis and Christoph Trattner then followed with the intriguingly entitled presentation Je t’aime… moi non plus: reporting on the opportunities, expectations and challenges of a real academic-industrial collaboration.  They gave an honest and candid reflection of their expectations for working together and how some of their past experiences in other collaborations weren’t as successful as hoped.  It was great material that fed into the discussions later in the day.

Heimo Gursch then gave some Thoughts on Access Control in Enterprise Recommender Systems.  While his project is still in the early stages, he had quite a few experiences that he could share from working with industry partners from the perspective of an academic.  He was working on designing a system that would allow employees in a company to effectively share their access control rights with one another rather than relying on a top down authority to provide them.  It’s also the first time that I’ve seen a presenter give his car keys to a member of the audience.  I do hope that the got them back.

Maciej Dabrowski delivered an exciting presentation Towards Near Real-Time Social Recommendations in an Enterprise.  His team and him have been working on a cross-domain recommendation system that works in a federated manner.  It exploits semantic data from linked data repositories to generate recommendations that spans multiple domains.

Mark Levy, from our team here at Mendeley, then presented some of the work that he has been doing in a talk entitled Item Similarity Revisited.  The presentation was filled with useful advise from an industrial perspective on what makes a good recommender system.  He also explored the idea that simple algorithms may be more useful than complex ones in an industry setting, showing some impressive results to back it up.

Benjamin Habegger then took us on a rollercoaster ride exploring some of his successes and failures in his last startup, 109Lab: Feedback from a Start-up experience in Collaboration with Academia.  He reflected on many of his experiences co-founding a start-up and the learning from the mistakes that were made.  Although he worked with academia during the process, he wasn’t clear about the value that it actually brought.

Finally, Thomas Stone presented Venture Rounds, NDAs and Toolkits – experiences in Applying Recommender Systems to Venture Finance.  Thomas had some nightmare experiences with NDAs during his PhD.  So much so, that he’s still unclear what he has the right to publish in his thesis.  He also gave a nice introduction to PredictionIO, an open source machine learning server.

Discussion Groups

Once the presentations were given, everyone was invited think about the challenges and difficulties that they had faced in working in academic-industry collaborations and to write down some topics on a flip chart.  We then split into three groups and, using these topics as guidance, discussed the issues faced and presented some solutions.

A number of issues were identified including:

  • · Prototypes vs production code – do the partners know what is expected from whom?
  • · How to find the right partners
  • · Access to data (e.g. NDA issues)
  • · Evaluating systems
  • · Best practices

After the three groups discussed the points we all gathered back to share our thoughts and conclusions.  In general, we all seemed to share similar problems in making academic industry collaborations successful.  We discussed that there should always be a clear set of expectations agreed from the outset and that partners should know their roles.  Communication lines should be kept open and the spirit of collaboration encouraged.  What’s more, it can help to have members of the teams working together in the same physical location, even if it’s just for a brief period, in order to work well together.

Working in academic-industrial collaborations is hugely rewarding but it can be tough.  Finding the right partners who understand each other’s goals and constraints is important from the outset.  We can all learn from one another but we need to put in some effort in order to enjoy the rewards.

I’d like to thank everyone who put in the effort to make the workshop a success and, as I follow up the several e-mails that I’ve got, hope to start some new and fruitful collaborations!




New Release: Literature Search from within Mendeley Deskop

[Editor’s Note–We thought you’d like to know: this 2013 post is a bit dated. Find Mendeley’s updated search features here, and info about Mendeley’s other features in the Mendeley Guides.]

Often the most impressive thing about a new software release is infrastructural and not immediately apparent, but not this time! In our latest release, we have added one of our all time most requested features – literature search from Mendeley Desktop. Also included in this release are a few improvements to how Mendeley Groups work, making it easier to collaborate with others using Mendeley.

We’ve always had the vision of Mendeley Desktop and Mendeley Web working as parts of a whole, but there have been some gaps, perhaps most notably how research discovery works. For example, to search your existing collection of research, you’d use Mendeley Desktop, but to search for new research in Mendeley’s catalog, you would go to the website. With the latest release, you’ll see a new section in the folder tree in the left pane. Where there was previously a division between My Library and Groups, there’s now a new section for discovery tools, hosting a literature search tool and Mendeley Suggest, our research recommendation service which learns about your academic interests and recommends new research specifically for you. There will be more discovery tools coming to this space, but for now let’s focus on how to use catalog search from Desktop.

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