The Only Technology Linking the Sequence to the Literature
Through our unique technology, we connect OMICs sequences to literature
Starting from our OMICs and metadata integration framework we link sequences, experiments or cohorts to literature analysis driven by a bottom-up NLP approach.
We unveil valuable relationships by finding associations in structured and unstructured data. Through integrating and structuring OMICs layers and metadata we can capture all relevant associations and bridge the gap between sequence(s) and text documents.
This enables you to work with an integrative data-driven approach where you can associate your experimentally obtained data with literature sources. By connecting these knowledge domains we aid your hypothesis generation or validation, weighing all relevant associations in the process.
From Sequence to Insights
With BioStrand NLP Link, you can focus immediately on meaningful relationships in your data at sequence and text level.
We look at the data with a different mindset to curate the most insights from your data. Different from all other solutions in the market, we use a unique bottom-up approach to reveal all the valuable relationships hidden in your data.
Why Is BioStrand NLP Link Unique?
Linking the Sequence to the Literature
Start your research with what you already have: your raw sequence(s). Our solution can look at the literature to find any relevant associations with your sequence or experiment and enrich your results.
Unique Bottom-Up Approach
All the current solutions in the market use the top-down method to curate just the answer to your questions. What BioStrand does differently is reveal ALL the potential value in your data with an unbiased bottom-up approach.
Focus on Relevant Insights
Nowadays researchers have to invest heavily in ways to distill valuable insights from various (big) data sources. We bridge the important gap between experiment, data and literature to overcome the challenge of being data overloaded.
Be Inspired by Data to Find New Groundbreaking Hypotheses
BioStrand NLP Link helps you see the connections and interactions between genes, microbiomes or diseases and inspires you to generate new hypotheses and start new research.
Focusing on the most relevant data points and relations that exist between your experiment and prior knowledge is the first step in developing new insights. The more relationships that can be checked across knowledge domains in silico, the more specific your wet lab validation can become. This improves your success rate, saves you time, and increases your chances of uncovering new insights and potential new drug targets by taking ALL data and knowledge into account.
The Correct Bit of NLP Technology at the Right Time
Semantic-Driven Text Analysis
We utilize a semantics-driven approach to identify concepts in a text. As it works completely bottom-up, it is domain agnostic and entirely non-biased. In life science and clinical literature, capturing the complete semantically correct boundaries is the critical first step, as distinct concepts in these fields can constitute over 7 words.
Context-Driven Relational Elements
Relational elements make the connection between concepts. As concepts are correctly captured, the variability of context can be derived from the relational elements. A single concept can appear in multiple contexts like negations or uncertainty. To capture these complex triplet relations we make use of smart indexing methods.
Meaning-Driven by Smart Indexing
After correct word boundaries are set, it makes sense to combine powerful deep learning technologies to label the concepts. Greater value can be extracted by combining deep learning and other AI technology with dictionaries and ontologies. Our smart indexing approach perfectly facilitates the combining of multiple knowledge enrichment steps.