About LabKey Archives

Barriers to R&D Productivity: What’s Slowing Down My Research?

Posted on January 22, 2019February 9, 2024 by admin

High-Throughput Data Generation Requires High-Tech Data Management

Historically, one of the primary challenges faced by drug development teams was generating enough data to conduct authoritative research. Innovative technologies introduced over the last decade have all but solved this, but R&D teams now face an equally daunting challenge: efficiently managing and analyzing the massive amounts of data produced by high-throughput technologies. These technologies have outpaced the data management systems of many organizations, creating a bottleneck at the point of analysis and slowing R&D productivity.

Team-Based Science Brings Data Sharing Challenges

The shift to team-based approaches in research has also compounded the challenges of handling massive datasets. For maximum productivity, teams must work across disciplines, which often means sharing data with geographically dispersed team members and collaborators. Some of the common challenges that arise in this type of high-volume, collaborative environment include:

The lack of a central point of access for data generated across team members.
The lack of visibility into what data has already been generated.
The lack of a reliable method for handing off data to other team members.
The lack of automated data integration tools, requiring team members to manually integrate data from multiple sources.

While some of these challenges can be solved through well documented processes and communication standards, LabKey Biologics is specifically designed to enable this type of team-based science. Over the course of the next few months, we will be discussing each of these barriers, the challenges they cause, and how R&D teams can overcome them with the help of LabKey Biologics. Subscribe to the LabKey blog to follow along.

[vc_cta h2=”Explore LabKey Biologics” h2_font_container=”color:%23116596″ h2_use_theme_fonts=”yes” h4=”Sign-up for a free, hosted trial.” add_button=”bottom” btn_title=”Start Trial” btn_style=”custom” btn_custom_background=”#779e47″ btn_custom_text=”#ffffff” btn_shape=”round” btn_align=”left” use_custom_fonts_h2=”true” btn_link=”url:https%3A%2F%2Fwww.labkey.com%2Flabkey-biologics-trial-sign-up%2F|||”] Explore LabKey Biologics free for 30-days in a secure, hosted environment. Sign-up for a LabKey Biologics trial to explore sample data, register entities, create samples, and more. [/vc_cta]

How-To’s of Managing Flow Cytometry Data

Posted on January 15, 2019June 10, 2024 by admin

Flow cytometry data is widely used across diverse set of research areas including drug discovery and personalized medicine. Ongoing improvements to instrument technology allow scientists to generate more and more targeted reagents which in turn leads to increasing amounts of high-dimensional flow cytometry data. As the application of flow cytometry in immune monitoring becomes more prevalent, many scientists are finding themselves asking “what is the best way to manage flow cytometry data?”

As teams evaluate software tools for managing flow cytometry data, there are several things to keep in mind. Instrument-generated fcs files from cytometers are generally not useful to scientists on their own. Typically, users interrogate their data by creating an analysis file, either with manual gating through commercially-available tools like FlowJo and FCS Express, or by performing computational analyses via free software packages like Bioconductor. Ensuring that data provenance is maintained between fcs files and analysis is vital, and provides valuable information for groups looking to validate or re-analyze the raw data in the future.

Maintaining Comprehensive Data Records

The LabKey Server software platform help groups ensure data provenance and maintain comprehensive flow cytometry records by:

Allowing for import of raw fcs files as well as analysis files
Validating all fcs files are present when linking data to a FlowJo workspace file
Auditing file upload for analysis data used in a LabKey study
Surfacing run parameters and compensation values for further quality control

Adding Value to Runs

LabKey Server’s flow cytometry tools can also helps add value to runs by:

Providing mechanisms to insert keywords and adding metadata
Ensuring gate naming is consistent across workspaces
Allowing administrators to merge gating strategies when necessary
Visualizing statistics in Levy-Jennings plots for valuable quality control metrics

Improving Data Analysis Workflows

Using LabKey Server, scientists can achieve further improvements to their analysis workflow by:

Integrating flow cytometry statistics and 2D plotting within the LabKey Server platform
Creating easy integration mechanisms across flow cytometry runs, panels, and projects
Providing built-in visualization tools for users to interrogate their data

With the right tools, scientists can maximize the insight derived from their flow cytometry data. To learn more about using LabKey Server to manage flow cytometry analysis, check out the flow cytometry documentation library or request a demo.

Your Success is Our Mission: Vision 2019

Posted on January 14, 2019September 1, 2023 by admin

A year ago, we set some big goals for LabKey and shared them on this blog. These goals have guided our development decisions over the last 12 months and helped us deliver many valuable features and platform enhancements to the 500+ organizations using LabKey solutions to power their research.

2018 Development Highlights

One of our key goals for 2018 was to expand the platform’s feature set to support key scenarios we were consistently hearing from customers. This led to the addition of a number of new features in 2018, with a particular emphasis on support for HIPAA, FISMA, and CFR Part 11 compliance, expansion of our support for the RStudio and RStudio Pro analysis packages, and the automation and expansion of data acquisition options through pipeline file watchers, a new ETL user interface, and integration with cloud storage providers.

Another key goal for LabKey’s 2018 development was to deliver on the functional roadmap for the LabKey Biologics product. The LabKey Biologics team added a suite of features to help teams organize experiment data as well as improvements to the usability of existing features.

Our final focus of 2018 was to strengthen both the backend technology infrastructure and the front-end user interface of the core LabKey platform. The LabKey team implemented a number of important security features including anti virus scanning, CSRF protection, captcha, API keys and spam protection for message boards to ensure the platform’s on-going security. We also implemented and tested support for the latest versions of all key dependencies (OpenJDK 11, PostgreSQL 11, Tomcat 9, SQL Server 2017, MySQL 8.0).

Read 2018 Release Notes: 18.1 Release | 18.2 Release | 18.3 Release

2019 Vision

As we kick-off 2019, LabKey is continuing to look to users for feedback and development direction. Building on the success of feedback collection efforts made in 2018, we will introduce new ways for users to review and respond to development plans to ensure they align with real-world workflows.

Core areas of focus for 2019 development include:

Sample Management

Sample management is an area of major investment and feature expansion for 2019. Building on LabKey Server’s existing foundation of sample management features, the LabKey team is working to develop a suite of new capabilities to support the registration and structured collection of sample related data, tracking of sample lineage, and facilitation of laboratory workflows.

UX Improvements

In Fall of 2017, LabKey introduced a redesigned user interface that significantly improved the look and feel of the LabKey Server interface. This year we are focused on enhancing the usability of the platform; identifying and improving common workflows that currently provide a difficult experience for users. Our initial focus area of focus is on improving the data import experience, simplifying the process of integrating data into LabKey.

Analytics Tool Integration

New support for integration with popular external analytics tools will be added over the course of 2019. Support for Tableau, Microsoft Access, and Microsoft Excel via ODBC is currently in active development and scheduled for release as part of LabKey Server 19.1 in March. These tools were selected as the result of a user feedback survey that was distributed last Fall.

Technology & Process Enhancements

Since LabKey’s inception as a standalone company, supporting our customers with a stable and reliable technology foundation has been a key priority. In 2019, we are making significant investments to upgrade our tools, libraries, and processes to leverage cutting edge software technologies in the products we deliver and to keep our team efficient. We are fully embracing technologies like Git, React, and Selenium 3, and recently transitioned our development process from Scrum to Kanban to increase the team’s productivity and transparency, and respond more rapidly to our customers’ requests. The team will also implement support for upcoming dependency releases including OpenJDK 12/13, SQL Server 2019, and PostgreSQL 12 as they are introduced throughout this year.

As we ramp up development efforts in 2019, we encourage you to engage with us. Your success is our mission, and as such, it critically important that we understand how we can enhance and evolve the LabKey Server platform to best support you.

Adam Rauch

VP of Product Strategy

Watch Adam’s “LabKey Update” presentation from this year’s LabKey User Conference for a full recap of 2018 and what’s coming in 2019.

LabKey Then & Now: GeekWire Highlights LabKey’s Evolution

Posted on December 28, 2018November 9, 2023 by admin

Long-time partners of LabKey know our story well; born out of Fred Hutch, the LabKey platform was developed to help research teams make sense of the large volumes of research data being generated by high-throughput proteomics analysis techniques.

While our mission is still the same, the platform has greatly expanded over the last 13 years to support new data types, analysis methods, and research disciplines from rare disease investigation to large-molecule drug development. In their recent article, GeekWire highlights LabKey’s evolution from a 3-person team in a Fred Hutch office to the self-sustaining solutions provider we are today.

LabKey’s motivation hasn’t changed a bit. “Every one of our customers you would want to be wildly successful,” said [LabKey CEO,] Michael Gersch. “Because they’re helping humanity. That’s what’s so neat about what we get to do.”

Read the full article on GeekWire.com to learn more about the history of LabKey and our vision for what’s next.

Original Article
Thorne, James. “How Fred Hutch spinout LabKey bootstrapped its way to compete in health care’s big data.” GeekWire, December 28, 2018, https://www.geekwire.com/2018/fred-hutch-spinout-labkey-bootstrapped-way-compete-health-cares-big-data/

Increasing R&D Productivity with Central Research Management Tools

Posted on December 12, 2018June 10, 2024 by admin

Team-based approaches to research are becoming increasingly popular in R&D labs as collaborative efforts help increase overall productivity and drive deeper insight. Research managers are responsible for ensuring that research activities executed by multiple team members operate efficiently and produce high quality results. In a multi-person environment, it can be challenging for research managers to achieve a comprehensive view of the all activities in their lab as data can easily become siloed.

As team-based research becomes more critical in science, research managers are in need of productivity tools that help facilitate communication and collaboration amongst lab members and provide them with a comprehensive look at their lab’s overall operations. LabKey Biologics provides a centralized system for managing of ongoing research and storing completed data analyses generated across team members. Some of the key tools to support team-based science include:

Configurable Work Request System

A configurable system for requesting work within LabKey Biologics facilitates the generation of work requests, their assignment, and the handoff of any resulting data for common laboratory tasks like sample preparation or assay data collection. LabKey Biologics maintains a persistent relationship between the task request and the resulting data, providing team members with helpful context about the data’s generation. For example, a user can easily navigate from an assay data grid within the system to the original request for the data, allowing them to see who requested this data and why. Specific samples, as well as, registered entities like protein sequences or cell lines, can also be tied to unique work requests.

Task Management for Bench Scientists

When tasks are assigned to users within LabKey Biologics, they are added to a dynamic workflow dashboard for that user. User-specific dashboards display tasks that are in that user’s work queue, as well as the tasks that they have assigned to others and their statuses. Research managers can use this dashboard view to monitor team member workloads, understand instrument usage, and plan for the future needs of the lab.

Experiment View of Assay Data

In order to keep experiments on track, research managers need the ability to see all of the analytical data that has been generated for each experiment. LabKey Biologics makes all assay data relevant to an individual experiment available directly from the experiment detail page. Users can easily search, sort, and filter integrated assay data for easy location of specific analytical results.

See how LabKey Biologics can help your team work together more efficiently and derive powerful insight from your integrated data. Explore LabKey Biologics free for 30-days in our hosted trial environment, or contact us to request a demo.

Built for Science: Pooling Data for a Better Understanding of Rare Disease

Posted on November 27, 2018February 3, 2025 by admin

Rare diseases are broad in phenotypic traits and far reaching in impact. Today, approximately 7,000 different rare diseases affect an estimated 350 million individuals worldwide.¹ Difficulty in the understanding, diagnosis, and treatment of rare diseases stems from a lack of available data about any one disease at any one research site. The volume of data needed to produce authoritative discovery about any one rare disease requires the collaborative pooling of phenotypic, genotypic, and clinical information from many disparate sources.

LabKey is helping research networks advance understanding about rare diseases by providing a flexible data management platform to help overcome key data integration challenges including:

Integrating Data from Multiple Clinical Sites

Researchers and clinicians need access to a substantial pool of data in order to identify disease trends and determine appropriate treatment for patients. In the case of rare disease where the occurrence of a disease within the population is not commonly seen, integration of data from multiple clinical sites is essential to identifying a patient’s course of treatment.

LabKey Server facilitates the collection and integration of rare disease data from multiple clinical sites by providing:

Operational data portals for data collection and preparation at clinical sites.
Data processing pipelines for transferring data to an integrated repository.
De-identification of personally identifiable information in clinical datasets.

Achieving Consistent Data Structures for Disease Data

In order for data to be integrated in a meaningful way, data generated at each clinical site must follow a consistent data structure. When data is structured correctly, researchers can query across data sources identify patterns in disease.

LabKey Server provides tools to help teams structure rare disease research data correctly during collection, and QA features to combat human error including:

Data entry forms for clinical data collection tied to underlying data structures.
Spreadsheet templates for offline data collection and bulk upload to LabKey data structures.
Quality control features like lookups, aliases, and validators identify and correct errors found in data prior to integration with other sources.

Providing Access to Integrated Data

Integrating data collected from patients of rare disease helps clinicians make data-driven treatment decisions and research teams understand the genesis of the disease and the potential pathways to its cure. The data access needs of these different interest groups often vary, and the ability to control access to data at a granular level is essential to maintaining patient privacy without hindering research progress.

LabKey Server provides tools to control access to rare disease data and ensure appropriate use including:

Role and group-based permissions for managing access to projects and folders.
The ability to flag and remove PHI fields from data sets for collaborators without PHI-level permissions.
An audit log that captures all access of and actions taken against a dataset.

[vc_cta h2=”Explore LabKey Server” add_button=”bottom” btn_title=”Start Your Trial” btn_style=”custom” btn_custom_background=”#779e47″ btn_custom_text=”#ffffff” btn_shape=”round” btn_align=”left” btn_link=”url:https%3A%2F%2Fwww.labkey.com%2Ftrial-sign-up%2F|||”]With the right tools, research networks have the ability to more effectively understand and treat rare disease. Sign-up for a free trial to see how LabKey Server can help your team overcome these and other key research challenges.[/vc_cta][vc_custom_heading text=”Related Resource” font_container=”tag:h1|text_align:left” google_fonts=”font_family:Roboto%3A100%2C100italic%2C300%2C300italic%2Cregular%2Citalic%2C500%2C500italic%2C700%2C700italic%2C900%2C900italic|font_style:300%20light%20regular%3A300%3Anormal” tm_text_transform=”uppercase” css=”.vc_custom_1541533930179{padding-top: 10px !important;padding-bottom: 10px !important;}”]

Blog Post

Genomics England and LabKey: Creating and Securing “A Dialogue Between the Clinical Context and Researchers”

Genomics England has been working with LabKey to develop a LabKey Server-based data management and exploration portal that would facilitate the knowledge sharing dialogue between clinicians and researchers as part of the UK’s 100,000 Genomes Project. The initial phase of this collaboration centered around providing clinicians and researchers access to centralized phenotypic and sample information gathered from rare disease patients and their families at sites across the UK while ensuring security and privacy of patient information.

Read the Post >

¹https://globalgenes.org/

The Java Shake-Up: What it Means to LabKey and You

Posted on November 16, 2018June 10, 2024 by admin

LabKey Server is a Java-based web application. Recent changes to Oracle’s Java licensing model and release schedule require changes by software providers like LabKey, as well as application administrators. Below LabKey’s VP of Product Strategy, Adam Rauch, explains the recent changes, how LabKey plans to address them, and what actions need to be taken by teams running LabKey Server to ensure on-going stability and support.

Recent Changes to Java Release Cadence and Licensing

Last year, Oracle announced several significant changes to the Java release and support model that introduce complexity to the previously straightforward process of deploying a Java runtime. Organizations will need to make decisions and revise their upgrade processes, but we believe these changes will lead to a stronger Java platform, one that will be more responsive and easier to support in the long term.

Perhaps the biggest news is that Oracle now requires a paid subscription for all use of the Oracle Java Runtime (“Oracle Java SE”) in production environments. Starting with Java 11 (released September 2018), organizations are required to pay up to $25 per CPU per month for production server or cloud use of Oracle Java SE. This seems to apply to everyone… no exceptions for academic, non-profit, or small organizations. With a subscription, Oracle will provide long-term support (LTS) for designated versions of their runtime (Java SE 8, 11, 17).

With Java 9, the release cadence transitioned from major versions every five or six years to more incremental feature releases every six months. According to Oracle, this new time-driven release model allows more rapid innovation, but it also means organizations will need to upgrade more quickly to keep pace with the changing platform.

This diagram (brought to you by the LabKey Visualization API) helps illustrate this change, with each bar capturing the time Oracle publicly supported (or plans to support) each version:

Note that in addition to more rapid and shorter releases, Oracle has eliminated the overlap between versions. Under the new model, public support for previous releases ends immediately upon release of a new version. As a result, Java 9 was end-of-lifed (no further support) the day Java 10 was released and Java 10 was end-of-lifed the day Java 11 was released.

Other Options and LabKey’s Response

As a Java-based web application, every deployment of LabKey Server is affected by these changes. You can certainly move to a paid subscription with Oracle, but many of you have told us you want a free Java option. LabKey has heard you and, starting with LabKey Server release 18.3, you now have the ability to deploy with a completely free, open-source Java runtime.

This is possible because Oracle has embraced OpenJDK, the open source implementation of the Java platform. Oracle recently contributed its remaining commercial features to the OpenJDK project and now builds its subscription Oracle Java SE from the OpenJDK sources. In fact, Oracle distributes two versions of OpenJDK: the Oracle Java SE requiring the commercial license and a production-ready open-source build of OpenJDK licensed under GPLv2 with the “Classpath Exception” (“Oracle OpenJDK”). The code is the same; the Oracle OpenJDK distribution merely lacks the long-term support provided under the subscription. Oracle might add proprietary enhancements (e.g., advanced garbage collection algorithms, just-in-time compilation, profilers, and other tools) to future commercial runtimes, but at the moment, these distributions should be interchangeable.

In response to these changes and our clients’ requests, LabKey has shifted our development, testing, and hosting to focus on Oracle OpenJDK 11. We will continue limited testing on the commercial Oracle Java SE releases, but the vast majority of our attention will be focused on OpenJDK. We plan to support future OpenJDK releases at or shortly after they’re released. Where possible, we’ll hotfix the current production release of LabKey Server to ensure it’s compatible with newly released versions of OpenJDK. (For example, even though it won’t be released until March 2019, we’re already testing OpenJDK 12 early-access builds against our 18.3 and pre-19.1 builds.)

Since older OpenJDK releases will not receive public support from Oracle (i.e., no security patches), LabKey will stop supporting them shortly after they’re end-of-lifed. To ensure you have all the latest Java security patches and bug fixes, you must regularly upgrade to the latest Java runtime release. You’ll need to upgrade to each six-month feature release plus the intervening security releases (two or three per feature release… roughly every two months).

Based on the published Java release schedule, Java support in LabKey Server for the next year will likely roll-out as follows (where “Java X” means “OpenJDK X and Oracle Java SE X”):

LabKey Release	Java Versions Supported	Changes
18.3 – Nov 2018	Java 11, Oracle Java SE 8	Add Java 11
19.1 – Mar 2019	Java 11 & 12	Add Java 12, Remove Java 8
19.2 – Jul 2019	Java 12	Remove Java 11
19.3 – Nov 2019	Java 12 & 13	Add Java 13

You can always visit our Supported Technologies page to review the latest plan.

Since OpenJDK is a true open-source project, many organizations other than Oracle are now building, distributing, and supporting it. A few of the most prominent examples:

AdoptOpenJDK has promised community-driven LTS builds of OpenJDK
Red Hat and other Linux distributions provide and support OpenJDK
Azul Zulu, IBM, SAP, et al offer free and commercial options
Amazon recently announced Corretto, a no-cost distribution of OpenJDK that includes long-term support

All of these implementations derive from the same OpenJDK source, so, in theory, they should be interchangeable. However, it’s important to understand that LabKey has not yet tested any of the non-Oracle distributions and, therefore, we do not support them. We plan to test more of these distributions over the next year. But for now, you will need to utilize one of the two Oracle distributions.

Recommendations for Your Team

It’s time to take action on these changes. Java 11 is here and Java 12 is coming soon. Java 8 will reach “End of Public Updates” for commercial users in January 2019, and will stop being a viable option for most deployments. Our recommendations:

Discuss Java licensing with your legal, licensing, and IT teams. They may have already put in place a runtime subscription or developed a policy around Java. If not, they need to understand these changes and create a plan.
Based on your organization’s policies, choose the runtime that’s appropriate for your deployments going forward: Oracle OpenJDK 11 or Oracle Java SE 11.
Upgrade to LabKey 18.3 and then switch to that Java 11 runtime.
Keep upgrading your runtime… every two months to stay secure.
If you’re building Java modules, switch your development and testing to JDK 11. IntelliJ makes it easy to configure multiple JDKs and switch between them, if you still need to build with JDK 8 for other work.

Comments? Suggestions? Questions? Please share them on the LabKey support forum .

What’s New in LabKey Biologics

Posted on November 16, 2018June 10, 2024 by admin

Over the past few months, the LabKey team has made several key enhancements to the LabKey Biologics application to help teams organize and visualize data relationships. Take a look at some of these recent enhancement below.

Group Sample and Assay Data Using the Biologics Experiment Framework

An experiment framework has been added to LabKey Biologics that allows users to group all the data relevant to a single experiment. Teams can define a name and description for each experiment, add samples, and upload analytical results.

Navigate Between Generations of Samples with the New Lineage Grid View

In addition to the existing lineage visualizations, LabKey Biologics users can now view all of the ancestors and descendants of a particular sample in an easy to navigate lineage grid. This grid view is particularly helpful when viewing lineage data for samples with large quantities of related samples or lengthy derivation history.

Auto-Register Sequences During GenBank File Import

Improvements to LabKey Biologics import process enable to the auto-registration of multiple sequences when a GenBank file is uploaded. With these changes the full sequence of the plasmid, the coding sequences, and the resultant protein sequences are now auto-registered.

Want to see these features in action

Explore LabKey Biologics free for 30-days in our hosted trial environment, or contact us to request a demo.

Built for Science: Data Sharing in Emerging Infectious Disease Research

Posted on November 6, 2018June 10, 2024 by admin

Emerging infectious diseases rapidly rise to prevalence and spread quickly across a population. In order to minimize their impact on public health, scientists must reach across geographical and organizational boundaries to share data that will help the global research community understand, contain, and ultimately cure aggressive infectious diseases. This type of large scale collaboration requires a robust research platform to centralize data and facilitate the shared generation of insight.

LabKey is helping teams around the globe combat emerging infectious diseases by providing a web-based data management platform to help overcome key collaboration challenges, including:

Integrating Heterogeneous Data

Scientists, public health officials, and medical professionals must be able to collect and integrate data from multiple sources (clinics, labs, etc.) in order to develop a comprehensive understanding of an emerging infectious disease. By housing data in one centralized location, researchers and collaborators can improve pathogen tracking and disease surveillance.

LabKey Server facilitates the collection and integration of data from a variety of sources by providing:

Specialized import tools to integrate data from a variety of immunoassay types, including ELISA/ELISpot, luminex and flow cytometry
Demographic datasets to capture metadata about individuals within a population
A study framework that connects demographic, clinical, and analytical data in order to monitor the disease and/or treatment status of individuals over time

Creating an Adaptable Database

During the early stages of a disease outbreak data is collected rapidly and abundantly. As the scientific community’s understanding of a disease increases, the data collection needs of researchers will shift as they determine which pieces of information are most valuable. The central data management system used by infectious disease researchers must provide both high levels of flexibility and structure in order to keep up with these broad and evolving data needs.

LabKey Server provides a highly flexible environment for data capture, allowing teams to evolve their research environment using:

A configurable and customizable user interface
Powerful query tools to merge and present data
APIs to import data from a wide variety of external sources and formats

Real-Time Data Sharing

In recent years, researchers working in the field of emerging infectious disease have begun to forgo traditional data publishing processes during times of a public health crisis, in favor of real-time data sharing. Real-time sharing of research observations and analytical data is helping accelerate the pace of understanding and development of treatments for aggressive infectious diseases.

LabKey Server facilitates real-time data sharing by providing:

Study publication tools that allow research teams to curate and publish public-facing datasets without compromising the security of their original data
Dynamic or static reports and visualizations to quickly summarize data for collaborators
Easy export of data to common research formats for ancillary investigation

[vc_cta h2=”Explore LabKey Server” add_button=”bottom” btn_title=”Start Your Trial” btn_style=”custom” btn_custom_background=”#779e47″ btn_custom_text=”#ffffff” btn_shape=”round” btn_align=”left” btn_link=”url:https%3A%2F%2Fwww.labkey.com%2Ftrial-sign-up%2F|||”]With the right tools, research teams have the ability to more rapidly understand and eradicate emerging infectious disease. Sign-up for a free trial to see how LabKey Server can help your team overcome these and other key research challenges.[/vc_cta][vc_custom_heading text=”Related Resource” font_container=”tag:h1|text_align:left” google_fonts=”font_family:Roboto%3A100%2C100italic%2C300%2C300italic%2Cregular%2Citalic%2C500%2C500italic%2C700%2C700italic%2C900%2C900italic|font_style:300%20light%20regular%3A300%3Anormal” tm_text_transform=”uppercase” css=”.vc_custom_1541533930179{padding-top: 10px !important;padding-bottom: 10px !important;}”]

User Presentation

Real-Time Open Data Sharing of Zika Virus Research Using LabKey

The laboratory of David O’Connor at the University of Wisconsin-Madison has been at the forefront of Zika virus research since the disease’s 2015-2016 outbreak in the Americas. The laboratory conducts studies with non-human primates to establish the natural history of infection and create a model that can be used to target future vaccine development. A key component of the lab’s work is the usage of the LabKey Server platform for real-time open data sharing of zika virus data with researchers worldwide and aggregation of diverse types of data that have been contributed by a large group of researchers into a central place.

In this presentation Michael Graham of the O’Connor lab shares how their team partnered with LabKey to provide open access to data during this public health emergency. Watch presentation >

Achieving Deeper Insight with a Consistent Analytical Data Structure

Posted on October 23, 2018June 10, 2024 by admin

Teams conducting protein-based therapeutic research use analytical data derived from molecular biology assays to assess the performance of protein targets. These often include simple measurements such as titer and amino acid measurements, as well as more complicated signal data assays like chromatography or differential scanning calorimetry. In order to effectively assess the performance of a protein, analytical scientists must be able to compare results across multiple assays.

Consistent structure of analytical data is essential for conducting this type of cross experiment analysis. LabKey Biologics provides essential tools to help protein engineering teams collect and centralize laboratory data with a structure that allows them to ask complex questions and a achieve deeper level of insight.

Configurable Assay Design Templates

Configurable assay design templates within LabKey Biologics provide a consistent structure for data being captured and ensure that each run of instrument data is stored in the same way. The use of a template for data capture prevents teams from accumulating data in independently designed spreadsheets when collected for each experiments and operator. Using an assay design template also allows you to indicate required fields, set data validation criteria, and normalize data as it is being brought into the central system.

Easy Mechanisms for Importing Data

LabKey Biologics provides several straightforward methods for loading data into these consistent structures. These include:

Automated loading of data via LabKey Biologics API
Manual uploading of files (.xls, .csv., .tsv)
Copy/Paste or typing into a textbox or grid

Data uploaded via these methods will populate the assay data structures discussed above, creating a structured catalog of analytical data for easy cross experiment analysis.

Powerful Querying of Sample Lineage

Consistently structured and centrally organized analytical data enables basic analysis and comparison of experiment results, but the real value of LabKey Biologics lies in the connection that the application makes between this data and the lineage of associated samples. Within LabKey Biologics users can view the lineage details of each sample; which bioreactor run a sample is derived from, what media recipe was used, or what molecule is was expressed. By connecting these details about sample context and physical characteristics to structured data about it’s experimental performance, protein engineering teams can significantly reduced the amount of analytical effort required to ask challenging questions of their data.

Explore LabKey Biologics free for 30-days in our hosted trial environment, or contact us to request a demo.