Bio-IT World Announces 2017 Best Of Show Award Winners
May 24, 2017 | BOSTON—Bio-IT World announced the 2017 winners of the Best of Show Awards Program to a packed audience at the Bio-IT World Conference & Expo. The awards program recognizes the best of the innovative product solutions for the life sciences industry on display at the Bio-IT World conference in Boston.
“The tools that enable drug discovery are evolving at such a rapid pace, it’s a treat each year to explore what’s new in our industry,” said Bio-IT World Editor Director Allison Proffitt. “The innovation on display by Bio-IT World exhibitors never disappoints.”
The Best of Show program relies on a panel of expert judges from academia and industry who screen eligible new products and hear presentations on site. This year our judges considered 47 new products, and viewed presentations on site from 16 finalists.
The judges named winners in four categories this year: Storage Infrastructure & Hardware; Analysis & Data Computing; Genomic Data Services; and Data Visualization & Exploration. Attendees also voted on the People’s Choice Award, selecting products that they believe measurably improve workflow or capacity, enabling better research.
The 2017 judging panel included Joe Cerro Richard Holland, Eleanor Howe, Phillips Kuhl, Mike Miller, Art Morales, Alex Sherman, Subi Subramanian, Bill Van Etten, and Proffitt.
The 2017 Bio-IT World Best of Show Winners Are:
Storage Infrastructure & Hardware
Starfish Storage, Starfish V4
Starfish is a suite of software modules that interact to create a holistic, managed storage environment.
The Starfish Core Catalog tracks the contents of conventional file storage devices and cloud-style object stores. Users and applications are able to associate metadata with files and directories, building awareness of the business and scientific value of the files. Starfish employs state of the art techniques to synchronize its database with file systems scaling into the billions of objects and Petabytes of capacity.
Rules Manager / Jobs Engine -- Starfish enforces rules by running scheduled batch jobs based on metadata values in the catalog. Jobs are run in parallel across a multitude of agents. Agents have built in functionality such as data migration and hash calculation, but they can also run custom code.
Report Engine -- Starfish has an interactive GUI allowing you to treewalk your filesystems, see recursive totals and aggregates at various levels of the tree. You can also query, find, and kick off jobs from within the GUI or generate more meaningful reports with utilization and trending details that are much more detailed that traditional tools as a result of the metadata values that can be used to define the result set.
Namespace Solutions -- Starfish metadata is the foundation for a global namespace that provides unique identifiers for all files and directories.
All modules interact through RESTful API. Thus, Starfish serves as a middleware for any data management solution that references files stored on conventional file systems and object stores.
Analysis & Data Computing
SciBite, SciBite LaunchPad
SciBite offers Semantics as a Service, available through its Java based restful API, with the following capabilities:
- Highly curated scientific ontologies, built upon open standards
- Formal based Named Entity Recognition
- Relationship mapping and extraction, identifying patterns
- Elastic Search of semantically rich data
- Live enrichment of browser based content
- Seamless connectivity to third party applications, providing search and connectivity
SciBite provides pluggable technology, so that you can integrate semantic enrichment exactly where you need it.
Fast, lightweight, and simple to use, we transform data by providing technologies that understand the scientific content they process.
Genomic Data Services
SolveBio, SolveBio Operating System for Molecular Information
SolveBio is a cloud-based operating system for molecular information that enables cross-disciplinary R&D groups to use complex multi-omics data from disparate sources to find biomarkers, stratify populations, and design clinical trials. SolveBio’s mapping technology transforms disparate internal and external data sources locked away in filesystems and databases into biomedical concepts such as variants, genes, patients, samples, and phenotypes through SolveBio’s entity extraction process. Data is formatted, indexed, and maintained by SolveBio’s cloud solution, then delivered by applications and APIs to the right people and the right workflows at the biopharma customer organization.
As a result, scientists are empowered to directly engage in data exploration and incorporate molecular data into decision-making without bioinformatics and IT support for data querying and visualization. Scientists can answer day-to-day questions on their data with easy-to-use web interfaces and familiar tools like Microsoft Excel and Google Sheets (through SolveBio plugins). SolveBio also seamlessly draws data from workflow engines such as DNAnexus and Seven Bridges, and moves clean, filtered data to visualization tools such as Spotfire and Tableau.
Data Visualization & Exploration
The Hyve, MatchMiner v1.0
Developed by Dana Farber Cancer Institute, in close collaboration with The Hyve, MatchMiner is an open source computational platform for algorithmically matching patient-specific genomic profiles to precision medicine clinical trials. The input is twofold: patient-specific genomic and clinical records, and structured eligibility criteria for clinical trials. Patient-specific information includes somatic genomic events, such as mutations, copy number alterations, and structural variants. Basic clinical data such as cancer type, age, and sex extracted from the Electronic Medical Record (EMR) are also transmitted. Structured clinical trial eligibility criteria includes the genomic and basic clinical criteria outlined in the trial protocol documents. The MatchMiner platform matches patient-specific genomic events to clinical trials, and makes the results available to trial investigators and clinicians via a web-based platform.
The software architecture of MatchMiner is divided into two main components to increase developmental flexibility. The MatchEngine is written in Python using the Eve framework to expose a RESTful API. All data is stored and indexed in several MongoDB collections. The frontend is written in AngularJS 1.5 using the Material Design components and philosophy. ElasticSearch is also used to facilitate searching of the data, enabling users to create customized aggregate search queries. MatchMiner supports all major browsers.
MatchMiner has currently won the Harvard Business School Kraft Precision Trials Challenge: http://www.hbs.edu/news/releases/Pages/matchmaker-wins-hbs-kraft-challenge.aspx
Seven Bridges, CAVATICA
CAVATICA lets researchers collaboratively manage and analyze data related to a number of rare diseases and cancers. Access control features allow for sharing of datasets of all scales. Researchers can search and view information about available datasets. When datasets of interest are found, users can request access directly from the data owners. Making data available to share and analyze in a single environment means that researchers can broaden their focus and make new connections beyond one disease.
CAVATICA promotes open standards using the Common Workflow Language (CWL). By integrating with CWL, analyses in CAVATICA are completely reproducible, and can be replicated in any environment with a CWL Executor.
CAVATICA is designed to appeal to users from a variety of clinical and research backgrounds. Users who prefer a graphic interface can use the platform via an intuitive website interface. A RestFul API allows for programmatic operation. Users can also bring their own tools to the platform using the open Rabix Software Developer Kit (SDK).
The SDK allows users to easily wrap existing tools for use in CAVATICA such that tools become fully portable, by first installing them inside Docker containers and the describing their behavior in accordance with CWL. Every facet of an application, including its command line arguments, runtime environment, parameters, and computational requirements are captured. Developing software with the Rabix SDK meant that there is no need to reconfigure existing command line tools to meet a proprietary format, and the tools remain runnable across a diverse range of infrastructures.