Bio-IT World Announces 2019 Best Of Show People's Choice Award Contenders

April 10, 2019

UPDATE: Voting is now OPEN

April 10, 2019 | Bio-IT World is pleased to announce the 2019 Best of Show competition with the Bio-IT World People’s Choice award.

The Best of Show Awards offers exhibitors at the Bio-IT World Conference & Expo an opportunity to showcase their new products. A team of expert judges views entries on site and chooses winners in four categories based on the product’s technical merit, functionality, innovation, and in-person presentations. The judges’ finalists are highlighted in the list of contenders.

In addition to the judges’ prizes, Bio-IT World presents a People’s Choice Award as well, which is chosen by votes from the Bio-IT World community. All of the Best of Show entries are eligible for the People’s Choice Award. Voting will open at 5:00 pm ET on Tuesday, April 16, and will remain open until 1:00 pm ET on Wednesday, April 17.

The four awards named by the judges and the People’s Choice Award will be announced at a live event on the Bio-IT World Expo floor at 5:30 pm on Wednesday, April 17.

We are excited to have the community’s input again this year on the best new products on display at Bio-IT World. Watch the Bio-IT World Twitter account @BioITWorld and #BestofShow19 for the voting link on Tuesday, April 17, at 5:00 ET.


2019 Bio-IT World Best of Show Contenders:

Basepair Inc | Booth 241

Product Name: Basepair; Version Number: 3.0

Basepair is a fully automated NGS analysis platform which includes highly scalable cloud infrastructure, validated workflows for all common NGS applications and interactive visualization and analytics. The NGS analysis pipelines for DNA-Seq, RNA-Seq, small-RNASeq, ATAC-Seq, ChIP-Seq, CRISPR-Seq, etc. Further, users may set up custom pipelines.

In addition to their web interface, they have an API that automates data ingestion. They provide integration for data import from BaseSpace, cloud, ftp servers, etc. Similarly, download of results can be automated using Basepair's API.

The analysis results are available in a fully interactive report which includes everything from QC, alignment metrics to tertiary results. All the visualizations are interactive, users may change the parameters dynamically and get the updated results within a second.

BC Platforms | Booth 617

Product Name: BC|PIPE NGS 1.0

The new product features optimize the base product, the fully automated, highly scalable NGS data secondary analysis pipeline called BC|PIPE NGS, for real world use cases. With the new developments, BC Platform's customers can:

• Run multiple pipelines (e.g. germline, somatic) within their platform, utilizing templates or building custom pipelines. The product allows for multiple pipeline validation, leveraging the same QC framework.

• Eliminate extensive manual intervention and automate the process of alignment and variant calling Exome or Whole genome data through the platform from machine to annotated file for analysis with integrated QC to ensure data quality across runs. Beyond secondary analysis BC|PIPE NGS supports tertiary analysis for variant annotation and interpretation within their app.

• Investigate any hanging or low performing jobs to take actions during execution through advanced performance metrics.

• Modify data analysis logic (WDL support) within the application, run code validation, and then test new logic against the published production pipelines through a new development interface

• Identify areas for performance improvement such as machine quality, sample fidelity, and pipeline efficiency. This information is available with metadata analysis so no individual data needs to be stored, bearing no PHI risk. Technology wise, this is run in a container infrastructure (Kubernetes for container management), and can run on Premise, in the cloud, or within a hybrid infrastructure allowing architecture fitting each customer’s requirements.

Finalist: Benchling | Booth 424

Product Name: Benchling Life Sciences R&D Cloud

The Life Sciences R&D Cloud consists of (1) a suite of six natively unified, browser-based applications hosted on AWS and built with Python and React and (2) an interconnected, bio-intelligent platform built on Amazon RDS and Postgres.

The Life Sciences R&D Cloud's six applications are Notebook, Molecular Biology, Registry, Inventory, Requests, and Workflows. This suite of applications, natively built for large molecule R&D, empowers scientist productivity, sample tracking, and R&D process management.

The Cloud’s bio-intelligent platform stores all types of R&D data, from DNA and protein sequences, to experimental results and metadata, to any custom objects the user defines such as animals, assays, and even greenhouses. In an industry first, this platform features bio-intelligent linkages that interconnect all R&D data to satisfy the complex experiment tracking needs of large molecule R&D. These bio-intelligent links automatically connect, for example, plasmid sequences to the physical locations of the cell lines that those plasmids generate downstream. As a result, scientists, managers, and executives can back up decisions with complete, interconnected experimental histories.

In addition, the Cloud can be configured for any organization's use case without any code. Since all changes to user permissions, data types, bio-intelligent links, workflow configurations, and more are all accomplished through a user interface, organizations can use the Cloud to drive rapid R&D process iteration.

BIOS IT | Booth 232

Product Name: Gene Genie

Gene Genie combines High-Speed Interconnect, Tiered Storage Arrays, GPU Accelerated Computed, Rapid Data analysis and an AI discovery engines within a single solution.

Causaly Inc | Booth 2

Product Name: Causaly Rapid Search V1

Causaly is releasing an Evidence Data Platform to make the research process in Biopharma more productive. Causaly does this by machine reading of Biomedical abstracts and closed-access full-text publications for linguistic causality. Evidence from Natural Language is then merged with evidence from 3rd party databases into the Causaly Knowledge Graph™. This graph contains more than 140 million points of causal evidence from more than 25 million academic publications and 10 databases. Scientists and decision-makers can intuitively search for evidence using Causaly's Rapid Search™ interface and analyze Mechanism of Action, Disease networks, Side effects, health outcomes and more within seconds, from global literature. Results are visualized and can be shared with colleagues for easy communication of complex topics. A variety of ontologies are used to ensure interoperability with existing systems and allow for connectivity to new data sources.

Finalist: Deloitte ConvergeHEALTH | Booth 526

Product Name: ConvergeHEALTH Deep Miner


Deep Miner runs on Amazon Web Services (AWS) and enables researchers to build and train their own disease-specific machine learning models, including deep learning models, using real world data (RWD). Building and training scalable and accurate patient level prediction models is heavily dependent on using an elastic, cloud-first approach. Deep learning methods have the potential to model thousands of parameters simultaneously more accurately than traditional, linear methods.

The Deep Miner module of ConvergeHEALTH Miner provides a scalable, repeatable framework for model development—including identifying the right cohort, generating a comparator, applying techniques to control for bias, and comparing various modeling techniques head-to-head to find the best performance for a specific hypothesis.

Discngine | Booth 636

Product Name: 3decision (V - 2018.11)

Officially launched in 2018, 3decision® is a first-in-class next-generation structural knowledge management solution. 3decision® provides cutting-edge structural analytics and a fully annotated and searchable structural database - all in a beautifully designed web-based user interface.

Collective & intelligent knowledge management In 3decision®, public & proprietary 3D protein structures and derived models are all automatically analyzed, organized and imported into a unique database. All users can easily access the same information, and share a new one, via a web browser.

The knowledge that has been generated over time by different project teams and research programs is fostered and can be applied to new projects. This allows each organization to maximize the value of the structural data and avoid situations where you end up reinventing the wheel.

Large-scale structural analytics 3decision® offers a series of state-of-the-art tools that allow scientists to efficiently perform large-scale structural analytics on the entire structural knowledge base. The tools are all adapted to first-time users of structure-based analytics but also allow the advanced user to tweak the parameters and push the analyses further.

The solution can be deployed on-premises or on a dedicated cloud-platform and is accessible through a standard web-browser. In addition to the UI, 3decision® exposes REST API endpoints that allow the integration of 3decision® analysis and registration pipelines directly within an organization's internal tools.

Finalist: Elsevier, Inc. | Booth 348

Product Name: Entellect

Entellect is designed to enable AI from the ground up. A stringent data governance process ensures that all content is brought into the platform in the richest form possible, and all aspects of data provenance is captured so users can know exactly what data they have access to. This also allows users to better assess the quality of each data source when conducting experiments.

Entellect connects content and makes data interoperable – through flexible aggregations which publish out to a variety of technologies for search/discovery, exploratory analytics and AI. In the case of AI applications, they have created an on-demand environment based on JupyterHub where users can work independently or in collaboration using a combination of public and Elsevier databases. In the case of search/discovery, Entellect harmonizes unstructured content from multiple different sources, supported by an Elsevier-developed API that can be consumed in a variety of healthcare applications.

EPAM Systems, Inc. | Booth 433

Product Name: EPAM Cloud Pipeline version 1.0

EPAM Cloud Pipeline is a specialized web-based cloud environment that provides the ability to build & run the customized scripts & workflows that support genomics analysis, modeling & simulation, and machine learning activities that are required to accelerate drug discovery research.

Cloud Pipeline is an Open Source platform that provides the following features and capabilities:

- Powerful, user-friendly Web interface.

- Support for multiple bioinformatics and modeling/simulation tools from an extensive library of Docker container images that are executed on cloud instances or clusters.

- Users can access active instances via Web based SSH connection, execute scripts, modify images by installing software packages, and commit modified images to the user’s personal repository.

- Ability to launch and manage interactive tools and applications with Web or Linux Desktop UIs.

- Users can build custom pipelines using a mixture of scripting languages, and save them to a built-in, version-controlled GitLab repository.

- Ability to create cloud storage units that upload and download data using a Web UI, Command Line interface (CLI) or by mounting storage folders to local Windows/Linux/Mac workstations.

- Ability to store and process data in multiple cloud regions.

- Management of data access permissions for both internal and external users.

- Support for thousands of users, utilizing thousands of nodes, and tens thousands of cores simultaneously.

- Support for single/multiple computation node configurations, as well as auto-scaled SGE clusters, MPI-based clusters, various CPU/GPU/Memory/Disks configurations.

- Protecting data using data-at-rest and data-in-motion encryption.

Finalist: Genedata AG | Booth 517

Product Name: Genedata Imagence 1.0

The new product presents a new deep learning based solution for phenotypic imaging and corresponding workflows based on convolutional neural networks. It yields improvements in automated image analysis for high content screens (HCS) including the ability to:

• rapidly detect and define all cellular phenotypes in an HCS;

• efficiently generate training data and on these train Deep Learning networks for subsequent classification of HCS image sets in production assays; and

• precisely quantify the relevant pharmacology.

The solution reduces time and costs required for phenotypic image analysis by generalization of expert input, producing quality results from a new experiment takes just seconds vs. weeks typically required by manual optimization with existing legacy systems.

The solution seamlessly integrates with Genedata Screener for detailed pharmacological assessment and profiling.

Finalist: Genestack | Booth 323

Product Name: Omics Data Manager

Omics Data Manager addresses the three major problems in biological data management—(1) data silos, (2) lack of metadata standards, and (3) unclear data relationships—by providing a modular set of tools and services for data FAIR-fication across life sciences R&D enterprises.

(1) Users can easily search both data and metadata across different locations via a fast, federated, and integrated search engine. This includes studies, samples, and multi-omics data (e.g. genomics, transcriptomics, and FACS). Search can be performed via a GUI interface with full-text and faceted metadata search, or programmatically, via REST endpoints and R/Python client libraries. In addition, access to multiple public repositories are available, such as GEO and ArrayExpress.

(2) Omics Data Manager harmonises metadata and enforces data standards via customizable metadata template, autocompletion, and validation using (public or proprietary) ontologies and controlled vocabularies, as well as expert-driven curation tools.

(3) Omics Data Manager tracks provenance of and relationships between entities such as studies, samples, and multi-omics data. Users can retrieve related entities effortlessly and explore the full context of each entity in order to make better-informed decisions on how to analyse, reuse or integrate data.

Finalist: Genomenon | Booth 217

Product Name: Mastermind Reporter

Genomenon uses Artificial Intelligence (AI) and Machine Learning (ML) to accelerate the literature curation process. The result is Mastermind, the most comprehensive database of genomic information in the world.

Mastermind automatically reads the titles and abstracts of every scientific medical paper published, over 30 million! The full text of papers with genomic information is then indexed to develop the most comprehensive view of the genomic landscape. To date, Mastermind has indexed the text of over 6.2 million genetic publications and covers over 4.1 million variants.

The genomic data found in the publications is processed through Genomenon’s patented Genomic Language Processing (GLP). More sophisticated than Natural Language Processing, GLP identifies every way that an author can describe a gene or variant and filters out erroneous information that can be mistaken for genomic data.

The data is then presented in a multi-faceted web interface, utilizing sophisticated algorithms designed to show the most relevant results first. Advanced filtering options allow the user to search broadly for maximal sensitivity or narrowly for optimal specificity.

The latest version of Mastermind includes Mastermind Reporter, a visualization tool that enables researchers to view, search, and filter large collections of curated data such as complete functional variant landscapes for solid tumor and heme oncology.

The Mastermind Genomic Search Engine, together with Mastermind Reporter, gives pharma and bio-pharma researchers the most comprehensive genomic landscape for any disease assembled from the published research for applications in drug discovery and clinical trial target identification.

Finalist: Globus | Booth 410

Product Name: Globus

The Globus service, used by thousands of organizations for research data management, now supports protected data, so scientists can easily work with this data and share it securely and appropriately with collaborators. This comprises management of Protected Health Information (PHI) including data regulated by the Health Insurance Portability and Accountability Act (HIPAA), Personally Identifiable Information (PII), and Controlled Unclassified Information (CUI).

With higher assurance levels for managing protected data, scientists can focus on new insights and discoveries, not on compliance and security concerns. As a result, researchers and teams can work together via approved, compliant methods on richer datasets that will enhance their research and accelerate the pace of discovery.

In addition, organizations have the option to enter into a Business Associate Agreement (BAA) with the University of Chicago, for written assurance that the data will be appropriately safeguarded by Globus in environments governed by HIPAA.

Invicro | Booth 613

Product Name: iPACS v.2.5 with Data Analysis Pipeline Tool

This tool takes advantage of modern approaches in data-processing workflows. It provides the ability to deploy user-made containerized and/or black-box analysis tools on any system accessible to the iPACS and call them directly on data sets from the iPACS user interface. Analysis tools read and write to the iPACS via a RESTful API and are deployed with simple remote procedure call (RPC) or Publish/Subscribe based client wrappers provided. Furthermore, these tools may be chained together as part of an automated pipeline. iPACS can be deployed in any on-prem, cloud or hybrid-cloud architecture. In addition, the iPACS can be implemented in a 21 CFR Part 11 and GxP compliant manner with full audit trail support. The iPACS allows custom form input, parameters from the database such as image meta-information and data points, as well as fixed job-specific parameters. Real-time generated authentication tokens are assigned and securely transmitted to the RPC server so that the remote procedure can create or update results back to the iPACS as the original calling user. The RPC server requirements depend on the remote program’s execution needs. RPC requests can be sent in batch as parallel executions.

Finalist: Kanda Software | Booth 311

Product Name: Trapelo

Trapelo is the only real-time precision medicine platform that enables everyone involved in cancer care to align their decision making and reimbursement policies with the most current clinical evidence in molecular oncology.

The platform features configurable practice, lab and payor modules that facilitate real-time, evidence-based decision support that lets oncologists know what to tests to order for which patients and from which labs, and then helps them interpret the results for more informed treatment decisions – all of this in the context of the patient’s insurance policies. This optimizes efficiency while giving oncologists confidence they’ve ordered the most relevant tests based on their patient’s disease and clinical stage.

Ensuring reimbursement policies are aligned with current evidence enables oncologists to make informed testing and precision medicine treatment decisions faster. Trapelo is more than a technology tool; it is a healthcare innovation that enables next generation cancer care to give patients the best possible chance to beat cancer. Trapelo is: Collaborative. Patient-centered. Continuously Updated. Actionable. Easy-to-use. Learn more here (

Finalist: Kanda Software | Booth 311

Product Name: LifePod Virtual Caregiver

LifePod’s Virtual Caregiver service expands the capabilities of popular smart speakers (e.g., Amazon’s Echo) with patent-pending innovations that make LifePod an easy-to-use, 2-way voice service for seniors or chronically-ill patients living at home and their caregivers. Unlike traditional voice assistants, LifePod can be set up and controlled by a remote caregiver using LifePod’s online Portal and Dialog Management System. In addition, LifePod’s unique “initiation” capability – enabling LifePod to speak to a senior without first being “woken” by the user – means the senior doesn’t have to remember a “wake word” or how to phrase commands in order to feel more connected and supported. Instead, LifePod provides proactive, voice-first check-ins and reminders each day, and encourages senior users to access voice services (e.g., music, weather, etc.) to enhance their day, based on routines configured online by their caregivers.

LifePod not only enables automated, 2-way voice control and communications but can also add new skills over time-based on the rich data collected via IOT sensors in the senior’s dwelling. Leveraging machine-learning and AI predictive analytics, LifePod will monitor the user’s condition, daily activities and behavioral trends (e.g., sleep, physical routines, medication, etc.) for anomalies or emergency events that can trigger a dialog with the user to collect more information and contact the caregiver directly, via a phone call or text message, as needed.

LifePod’s features:

For Caregivers: Configure proactive reminders, check-ins and easy access to online services for seniors aging-in-place and chronically-ill patients living at home.

For Seniors: LifePod’s AI-powered Virtual Caregiver offers proactive check-ins, reminders, fall detection and sensor-driven healthcare for remote monitoring, support, and connectedness.

Alerts and Reminders: LifePod also offers caregivers the ability to easily configure emergency alerts that will be sent via text, and provides daily reports, sent via email, that summarize activities for family members and the care giving team as needed.

What’s New:

In late 2018, LifePod announced a partnership with MobileHelp®, a leader in mobile Personal Emergency Response Systems (mPERS) that enables people to summon the help they need — be it a family member or an emergency response service — to their location by simply using their voice. The resulting partnership delivers the first fully-integrated, voice-enhanced, emergency response system and virtual caregiver while also providing a proactive solution for healthcare institutions that wish to add voice to their automated remote patient monitoring and voice-enabled response capabilities.

Lifebit | Booth 6

Product Name: Deploit - Beta

Lifebit is democratizing multi-omics, biomedicine & big data analysis with its AI-powered cloud-based system - Deploit. Deploit enables developers and researchers, no matter their computational or data analysis training level, and their corresponding organizations (ie. startups, SMEs, pharmaceutical companies), to instantly run and scale data analysis in a fast, cost-efficient and reproducible way. Deploit automates the analysis process, learns from the data, and provides actionable insights. Further Deploit enables easy sharing of analyses and seamless collaboration no-matter the size of your organization. As an Individual or a company, starting with Deploit requires zero onboarding and zero configuration... just log in, plug, play!

ONTOFORCE | Booth 324

Product Name: 2019 Linked Data Ingestion Engine

The new Data Ingestion Engine added to the existing faceted browsing and visual analytics engine in the DISQOVER platform contains the following:

- A performant and scalable Extract, Transform, Link, Infer & Load (ETLIL) engine, capable of creating massive amounts of links & performing inferencing.

- Using semantic concepts (RDF triples and ontologies) as a data reasoning model.

- Capable of performing ETLIL actions on massively linked data using commodity hardware (e.g. ~10 billion triples on single machine with 6 cores / 64Gb RAM).

- Managed by a graphical, component-based pipeline via a user-friendly frontend.

-Incremental updating of the pipeline when a data source gets updated

- Including full data transformation inspection capacities (both upstream & downstream).

- All combined with tolerance-based, process-oriented Quality Control (QC), usable for real-world data.

> Tolerance-based: no rigid schema is required

> Process oriented:

- incoming QC (verifying source data)

- within-process QC (verifying intermediate results) and

- outgoing QC (verifying end result data) can be specified.

Finalist: PetaGene | Booth 317

Product Name: PetaSuite Protect v1.0

PetaSuite Protect enables organizations to manage access to their genomic data by internal and external teams, secured with fine grain regional encryption and deep auditing of data usage. Moreover, this is done in a manner transparent to existing tools and pipelines and integrates with existing on-premises and cloud storage infrastructure.

The state-of-the-art prior to PetaSuite Protect is to grant access to users of genomic data on a whole-file or whole-object basis, which means the person it belongs to might be identifiable. While some file-systems support auditing of accesses by internal users, there is very little visibility into what users are doing with this data. And when granting access to external users, there is typically no visibility at all once the data have been transferred to them.

With PetaSuite Protect, users see regular genomic files. When they access these files, they only see the specific regions that they have permissions to view. PetaSuite Protect gives live information on the use of genomic data by those parties, and the ability to immediately grant or revoke access privileges.

Organizations can allocate GA4GH-defined data management roles. Every user access is logged in a tamper-resistant and easily searchable cryptographic ledger. Not only is user and file information recorded but also details of what application was used for access, and what genomic regions were read. Furthermore, decryption and decompression are performed on the client with a transparent high-performance library, rather than by the server. This ensures high scalability across multiple users.

Pure Storage | Booth 309

Product Name: AIRI

AIRI is the first AI-ready Infrastructure, architected by Pure Storage and powered by NVIDIA. AIRI is purpose-built to enable data architects, scientists, physicians and business leaders to extend the power of the NVIDIA DGX-1 deep learning server and operationalize AI-at-scale for life and health sciences organizations. It delivers a tightly integrated hardware and software platform out-of-box for AI, empowering valuable data scientists to focus on algorithms instead of infrastructure, and slashing time-to-insight from weeks to hours.

Engineered as a fully integrated software and hardware solution by Pure Storage and NVIDIA, AIRI eliminates infrastructure complexities that hold organizations back from deploying AI-at-scale – which is essential to accelerating the advancement and impact of personalized medicine. AIRI is powered by Pure Storage FlashBlade™, the industry’s first storage platform architected for modern analytics and AI, and four NVIDIA DGX-1 supercomputers, delivering four petaFLOPS of performance with NVIDIA ® Tesla ® V100 GPUs. These systems are interconnected with Arista 100GbE switches, supporting GPUDirect RDMA for maximum distributed training performance. AIRI is supported by the NVIDIA GPU Cloud deep learning stack and Pure Storage AIRI Scaling Toolkit, enabling data scientists to jumpstart their AI initiatives in hours, not weeks or months.

With AIRI, life sciences organizations can get started and see success more quickly, accelerating time-to-insight and potentially bringing new, impactful innovations to humanity, faster.

QIAGEN Bioinformatics | Booth 242

Product Name: Ingenuity Pathway Analysis with Analysis Match

Ingenuity Pathway Analysis with Analysis Match compares the biological signatures for each dataset a researcher analyzes in IPA against signatures of all their previous analyses and to those from more than 50,000 pre-analyzed comparison datasets curated by the QIAGEN company OmicSoft. These are not gene signatures, but represent the higher-level biology: what the expression changes are predicted to mean.

The raw gene expression datasets for IPA analysis are disease-relevant datasets downloaded from public data sources such as GEO, ArrayExpress, TCGA, and LINCS and completely re-processed and re-curated with controlled vocabulary in a reproducible pipeline.

From these >300,000 samples (so far), more than 50,000 comparisons have been created representing such types as “disease vs. normal”, “treated vs. untreated” or “tissue 1 vs. tissue 2”.

Each quarter, datasets are imported into IPA, analyzed, and published to IPA users. Biological signatures are automatically created for each analysis, consisting of the top predicted Upstream Regulators, Causal Networks, Canonical Pathways, and Diseases and Functions. Signature matches are computed and used to rank the analyses versus the query analysis. From the table of matching analyses, the user can sort and filter by metadata or scores and create a detailed heatmap to display the underlying reasons why their analysis looked similar (or nearly opposite) to other analyses. Recently added to Analysis Match were signatures based on metabolic pathway activation or inhibition, and many thousands more analyses, including the LINCS compendium of >28,000 analyses of well-defined compound treatments or other experimental manipulation of cell lines.

Qumulo | Booth 407

Product Name: Qumulo Hybrid Cloud File Storage, 2.11.1

Qumulo’s hybrid cloud file storage is an ideal solution for storing, managing and accessing genomic sequencing and research imaging data. Qumulo is a modern file storage system that can scale to billions of files and that runs in the data center and the public cloud.

Managing throughput and latency are critical for research imaging. Qumulo provides high performance, even with 3D image files that require random small block reads to access the image the researcher wants to see.

Qumulo real-time visibility and control provide information about what’s happening in the storage system, down to the file level, no matter how many files are in the system. Administrators can apply quotas in real-time, so they’re always in control of how resources are allocated. The capacity explorer and capacity trends tools give IT the information it needs to plan sensibly for the future and not waste money due to over provisioning.

Organizations that want to move some of their genomic analysis and research imagine workloads to the cloud can use Qumulo for AWS. Qumulo has the highest performance of any cloud offering and is the only file storage system in the cloud with a full set of enterprise features, such as multi-protocol support and real-time visibility.

Qumulo ships software every 2 weeks. This methodology, a tenet of Agile development, allows Qumulo to deliver software as soon as it’s ready instead of waiting for the end of a long multi-month cycle. This means that as new customer and market conditions change, Qumulo can reprioritize when it’s in its, and its customers, best interest.

Rescale | Booth 209

Product Name: Rescale ScaleX Platform

Rescale ScaleX is a platform for high performance computing in a multi-cloud environment. With more than 300 applications ported and tuned in the life sciences and other areas of science and engineering, Rescale enables users to select an application to run, or specify a more complex workflow, and it recommends where to run across multiple cloud providers and architectures, offering pay per use for hardware and software. The fully-managed turnkey solution offers security, compliance, budget controls so users can truly focus on science and engineering. The 2019 ScaleX platform offers enterprise capabilities, increased security, SOC 2 Type 2, HIPAA, and FEDRamp compliance equivalence, access to the latest CPUs and GPUs available, High Performance Storage and High Performance Desktops.

Riffyn, Inc. | Booth 247

Product Name: Riffyn Scientific Development Environment v3.0

Finalist: SciBite Limited | Booth 423

Product Name: CENtree 1.0

CENtree is a collaborative ontology building platform tailored to life sciences needs for both editing and browsing ontologies in one. Ontology browsing is oriented around a tree tailored to visualizing biomedical ontologies, their entities, and their relationships. Complex language associated with formal ontologies is replaced with user-friendly terminology. Ontology editing activates an overlay which makes the browser editable. Adding new classes and editing/enriching existing classes is simplified to enable a broader audience to contribute. Edits are captured using open standards to make the resulting ontology reusable elsewhere. A deep learning component helps a user to edit by suggesting possible relationship connections for a given class.

CENtree employs a Git-like approach to managing change with SciBite's custom versioning engine, empowering an organisation to keep current with the latest public versions, whilst internally adding new content such as extending with new classes or fixing errors. A one-click system simplifies loading public or private ontologies without custom parsers or web downloads. Provenance is captured for every edit action, with user comments to explain edits, and the ability to roll back from an undesired change. A governance model controls the ability to affect change through roles such as ‘suggester’ (can suggest an edit) and ‘editor’ (can make live edits and approve suggestions).

The CENtree interface is founded on a flexible API which can be directly integrated into existing systems. Combining the ontology management and semantic analytics capabilities of SciBite's platform offers a unique approach in managing scientific information in the journey to clean data.

Seven Bridges | Booth 332

Product Name: Enterprise Module

In the past year, Seven Bridges has introduced a multitude of platform enhancements to make data more available and actionable for a large set of users. By leveraging AWS Snowball, they enable Seven Bridges' customers a seamless and efficient bulk data migration to the cloud which allows all their data to be stored in one place and bypass the maintenance of the on-prem storage of historical data.

New data flows directly to the cloud, completing the migration. With historical and newly generated data in the cloud, organizations are able to enhance collaboration amongst researchers dispersed across multiple geographies and implement cost control mechanisms while maintaining privacy. Enhancements from Seven Bridges in the past year offer:

- Sharing of resources including, common tools, datasets, and references while simultaneously enabling privacy of individual assets across various levels of research groups within an organization

- Multi-cloud capabilities that allow researchers to analyze data where it lives

- Consistency and ownership of assets that are generated by different groups and users

- Secure asset management within a singular division by deploying a division-level repository of docker images and data resources that can be managed by an admin

- Data can be further organized into folders mimicking on-prem structure, enhancing interoperability

- Granular budgetary controls across various research groups within a single organization, inclusive of multiple payment options and spending limits

Finalist: Seven Bridges | Booth 332

Product Name: Graph Genome Suite

The human reference genome serves as the foundation for genomics by providing a scaffold for alignment of sequencing reads, but currently only reflects a single consensus haplotype, thus impairing analysis accuracy. Seven Bridges has developed a graph reference genome implementation that enables read alignment across 2,800 diploid genomes encompassing 12.6 million SNPs and 4.0 million insertions and deletions. The pipeline processes one whole-genome sequencing sample in under 5 hours using a system with 36 CPU cores. Using a graph genome reference improves read mapping sensitivity by 0.5% in variant calling recall, with unaffected specificity. Structural variations incorporated into a graph genome can be genotyped accurately under a unified framework. The additional technical specifications can be found in the recent Nature Genetics manuscript titled “Fast and Accurate Genomic Analysis using Genome Graphs.”

As a follow on to the recently published Nature Genetics manuscript, a newly released Common Workflow Language (CWL) 1.0 workflow for whole-genome sequencing (WGS) alignment and variant calling using the Seven Bridges graph-based technology showcases continued improvements in variant calling, especially indel detection, as well as the capability to detect larger deletions than competing callers. Advancements in the graph-based technology also showcase a reduction in runtime and cost when compared to similar linear approaches.

Univa | Booth 540

Product Name: Navops Launch 1.0

In November of 2018, Univa announced Navops Launch 1.0, the most recent version of the company’s powerful hybrid HPC cloud management product. Navops Launch meshes public cloud services and on-premise clusters to cost-effectively meet increasing workload demand. The platform was built to help HPC organizations manage cloud spending and audit usage, and allows them to optimize and balance application placement between hybrid cloud services and on-premise infrastructure. This gives enterprise users predictability, monitoring and control of their cloud expenditures. Enterprise customers are further equipped with an automation engine that integrates cluster and cloud management systems, with end-user defined metrics, to fully inform intelligent cloud workload placement actions.

Among the capabilities in Navops Launch is an intuitive web interface that makes it easy for cluster administrators to extend on premise clusters to their choice of cloud. Navops Launch also meets enterprise demands by providing easy integration into enterprise identity providers and interoperability with cloud authentication services. Enterprise cloud security teams are equipped for success through integration with cloud networking, name resolution, firewall, virtual networks, and support for “bring your own image” (BYOI) model that easily fits existing cloud images into a Navops Launch-managed environment. Built-in adapters exist for Amazon Web Services, Google Cloud Platform, Microsoft Azure and OpenStack to augment an organization’s multi-cloud strategy.

WASAI Technology, Inc. | Booth 506

Product Name: WASAI Lightning

WASAI Lightning-bwa is a BWT-based solution composed of memory-bound and computing-bound(Smith-Waterman) acceleration technology. They provide the same interface as native BWA-MEM does to make the user’s migration seamless. Lightning-bwa is fully integrated with Acer Altos R380 F4 server. When using Illumina Platinum-genomes NA12878 30x as benchmark, the WGS alignment only needs 2hrs with 2 FPGA cards and generates consistent result with native BWA-MEM. Here is the integrated Acer Altos R380 F4 server with below spec.

० CPU: Xeon® Gold 6138

० Memory: DDR4 128GB

० Storage: HDD 20TB; SSD 2TB

Among the capabilities in Navops Launch is an intuitive web interface that makes it easy for cluster administrators to extend onpremise clusters to their choice of cloud. Navops Launch also meets enterprise demands by providing easy integration into enterprise identity providers and interoperability with cloud authentication services. Enterprise cloud security teams are equipped for success through integration with cloud networking, name resolution, firewall, virtual networks, and support for “bring your own image” (BYOI) model that easily fits existing cloud images into a Navops Launch-managed environment. Built-in adapters exist for Amazon Web Services, Google Cloud Platform, Microsoft Azure and OpenStack to augment an organization’s multi-cloud strategy.

WekaIO | Booth 501

Product Name: Matrix v3.3

WekaIO Matrix is the only parallel POSIX file system that runs natively on NVMe flash technology to meet the I/O demands in throughput, latency and scalability for life sciences workloads. For applications with small files and high metadata demands, common in genomics, customers have seen a 10X performance advantage over legacy NFS based NAS systems.

Matrix software is optimized to leverage the speed and low latency of NVMe-over-fabrics technology to support both small and large file access - either randomly or sequentially – resulting in highest performance I/O. It is deployed on standard x86 server infrastructure from a variety of vendors including HPE, Dell and Supermicro. The software supports internal tiering to geo distributed object storage for massive scalability in a single namespace and its snap-to-object feature provides seamless disaster recovery. It is cloud-native allowing enterprises to leverage on-demand public compute resources for cloud-bursting and remote backup.

As proof of its leading performance, Matrix achieved #1 position in performance and latency across the complete set of SPEC 2014 benchmarks, the industry standard for file storage. It also achieved #1 position on the IO-500 10 node challenge, beating out the world’s biggest supercomputer parallel file system. It is ideally suited for performance workloads in life sciences, pharmaceutical R&D, and research labs.

Matrix features include:

• NFS, SMB, S3 and POSIX

• Tiering to object storage

• Snapshots

• Snapshot-to-object storage

• Security including:

o Encryption in flight and at rest

o Role based access control (RBAC)

o Active directory integration (LDAP)

• User Quotas

• Cloud-bursting

• Support analytics

Zifo Technologies Private Limited | Booth 404

Product Name: Sci-Desk 1.0

In the current technology landscape, the scientific systems are either built from scratch in the cloud or companies do lift and shift into the cloud, Sci-Desk is a cloud-based on-demand product offering comprehensive managed services for scientific & lab computing systems spanning discovery, R&D and manufacturing.