Professional Edition ELN - LabArchives Store, Organize, Share Laboratory Research Data The Professional Edition is for Principal Investigators, lab managers, post doctoral fellows and grad students. This edition will improve the productivity of research staff, finding information and recreating experiments. Try it. It's Free! or sign in Enhance your Team. LabArchives® is the leading secure and intuitive cloud-based Electronic Lab Notebook (ELN) application enabling researchers to easily create, store, share and manage their research data. Compatible Our Electronic Lab Notebooks work on multiple platforms and devices. Data Compliant LabArchives supports funding agencies data management plans requirements. University Partners Approved Service Provider for Internet2 higher education member universities. Replace the Paper Notebook to better monitor, engage and evaluate your teams' lab work Notebook user access can be managed to allow access rights to certain notebooks, pages and/or entries LABARCHIVES APPs IN ACTION get the iOS app! Sign up
Digital tools for researchers | Connected Researchers Find out how digital tools can help you: Explore the literature(back to top) Here is a collection of digital tools that are designed to help researchers explore the millions of research articles available to this date. Search engines and curators help you to quickly find the articles you are interested in and stay up to date with the literature. Article visualization tools enhance your reading experience, for instance, by helping you navigate from a paper to another. Search engines and curators Article visualization Find and share data and code(back to top) Managing large sets of data and programing code is already unavoidable for most researchers. Connect with others(back to top) Research cannot stay buried in the lab anymore! Connect with experts and researchers Outreach Citizen science Crowdfunding At the bench and in the office(back to top) Here is a collection of tools that help researchers in their everyday tasks. Lab and project management Electronic lab notebook Outsourcing experiments
Data guidelines Data Guidelines 1. Overview This page provides information about data you need to include when publishing an article in F1000Research, where your data can be stored, and how your data should be presented. A large number of journals and publishers have confirmed that they welcome research articles reporting analysis and conclusions that are based on previously published datasets: They do not consider the publication of a dataset with a DOI and associated protocol information as a ‘prior publication’ that would preclude subsequent publication of new results obtained from such a dataset. 2. All primary research articles should include the submission of the data underlying the results, together with details of any software used to process results. Data are normally published under the CC0 licence which facilitates data reuse. 3. 3.1 Spreadsheet data Give each column a descriptive heading. Embed charts, comments or tables within a spreadsheet. 3.2 Software source code 4. 3D-printable models
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How To Publish Like A Huge Content Creation Team (When It’s Really Just You) Generate dozens of ideas, publish daily and collect 830+ leads in 60 days...even if your site’s brand new. Apr 19th, 2016 by Niklas Goeke Don’t things like these make you want to punch something? If it were that easy to get 1,000 subscribers, wouldn’t we all be internet millionaires by now? You’re an email marketing expertYou have a massive, pre-existing audience. Of course you can just install a pop-up when you get 100,000 visitors a month and collect an easy extra 1,000 subscribers. But if you’ve never built an email list before and no one in your industry knows your name, you need somebody to take you by the hand and walks you exactly through what to do, step by step Lucky for you, that’s exactly what I’m going to do today. Getting my first 1,000 subscribers took me 6 months of: Trying every tactic and strategy bookWriting thousands of emailsSpending hundreds of hours on blog postsCreating countless content upgradesPromoting my work everywhere But it does get better. Want proof? Seriously. 1.
Docollab | Features Search, sort and filter With Docollab you can quickly find the content you are looking for. You can search by keywords and labels, filter your results by ownership and date, and sort them by name or date. Docollab projects help you organize your work and track overall progress Organize projects Docollab lets you organize your content in folders. Manage notebooks You can create notebooks in your projects and import existing notebooks. Manage tasks Project tasks can be assigned to any member of that project. Share projects As a project owner, you can add and remove members. Docollab notebooks help you take notes and document your work Rich text editing Docollab notebooks support a range of rich text capabilities. Table editing Aside of the tables which can be embedded in rich text sections, data tables provide a spreadsheet-like way to write and view tabular data, and support copy-paste operations from/to Excel and similar programs. Organize notebook pages Files, images and annotations Track changes
Sparrho | Latest Applications of Deep Learning Learning Informative Features from Restricted Boltzmann Machines Abstract: Abstract In recent years deep learning paradigm achieved important empirical success in a number of practical applications such as object recognition, speech recognition and natural language processing. A lot of effort has been put on understanding theoretical aspects of this success, however, still there is no common view on how deep architectures should be trained and thus many open questions remain. Pub.: 01 Dec '16, Pinned: 07 Dec '16