Sciome employs a highly talented team of software engineers and scientific programmers. This development team works closely with Sciome scientists, mathematicians and statisticians to design and implement interactive software solutions that solve important problems on behalf of our clients. Our services span the entire software development life-cycle, including requirements gathering, software architecture design, user interface design, implementation, deployment, maintenance and user support. Examples of our recent work include:
as well as all of the applications listed below.
DMR Generator Tool
Recent improvements in next-generation sequencing technology allow for the efficient, genome-wide measurement of changes in DNA methylation status. With diverse applications including novel research into the mechanisms, regulation and biological consequences of genomic imprinting, chromosomal stability and embryonic development, these technologies have opened up new frontiers in a multiplicity of domains including toxicology, pharmacology, medicine and genetics. Unfortunately, however, the statistical methods available for analyzing the resulting data have so far been quite limited, and to date there are few existing methods that can accurately identify differentially methylated regions (DMR) from raw sequencing data. To overcome this limitation, Sciome has developed DMR Generator, a web based application for conducting a bioinformatics analysis of whole-genome DNA methylation profiles. In addition, DMR Generator also provides the opportunity for integrated downstream data analysis of the results.
DMR Generator can be accessed here.
The ‘Flow-Intelligent Document Decoder for Literature Extraction’ (FIDDLE), is a novel algorithm and a tool under development, which can accurately extract text from scientific PDF documents. In addition to preserving the correct word order across columns, and even around figures and tables, FIDDLE is also able to accurately sectionalize scientific documents in an automated fashion. When key scientific terms (e.g. chemical names) are mentioned in different document sections (e.g. title, abstract, methods, references, etc.) they may carry greatly different implications. Therefore, the ability to correctly divide documents into meaningful sections is a critical capability in the context of literature mining.
When combined with a custom built, dictionary-based chemical name recognizer, FIDDLE is able to accurately extract chemical names from full text PubMed manuscripts at a rate several times greater than would otherwise be possible using only the associated MeSH terminology or the text of the titles and abstracts. Our approach offers the ability to perform full text extraction of scientifically relevant keywords (e.g. chemical name or phenotypic endpoint) and in turn greatly enriches text and literature mining capabilities with wide ranging applicability in the environmental and health sciences.
The Risk21 RoadMap is a web-enabled visualization tool developed at Sciome in collaboration with the ILSI Health and Environmental Sciences Institute (HESI). This tool automates the Risk21 framework for problem formulation and risk assessment, as developed by researchers at HESI. The Risk21 framework is a highly visual process for problem formulation and risk assessment that allows researchers to integrate available exposure and toxicology information in way that can be effectively communicated with a variety of stakeholders, including those without extensive training in the toxicological sciences. Sciome’s role in this project was to design and implement the software on behalf of the client. The resulting application, referred to as the Roadmap Risk21 Visualization (RRV) tool, is currently being utilized by hundreds of research groups across the globe. A number of stakeholder engagement and educational workshops within the US and around the world have also been conducted, focusing on the use of RRV for toxicological research.
The Risk21 Web Tool is available here.