Editorial Services
Data saturation is universal. With the exponential increase in data collection, it is critical to refine and manage data more than ever to ensure its meaningful application. Our Editorial & Author Services help optimize content and data to meet your specific requirements by harnessing machine learning (ML) and artificial intelligence (AI). Our Editorial & Author Services include:
Services
Developmental Editorial Services
Development Editorial Service focuses on the structure and buildout of data to ensure a clear message flow. It helps analyze the manuscript as a whole in order to make necessary edits. For instance, removing too much material where it is not required and feeding in more, where necessary. It concentrates upon content, flow, writing style, and presentation. All this, while keeping in mind the target audience.
Molecular Connections’ Development Editorial Service provides turnkey content production and distribution solutions to help you connect with your target audience. We contribute towards creating a seamless experience for your users across channels by delivering polished manuscripts, coupled with perfect marketability.
Molecular Connections A&I reach
Patents, Journal Articles, Books, Standards, Dissertations, Input as PDF, MS Word, HTML, XML
Around 6 million patent abstracts, including non-English patents
Over 100k abstracts of medical case reports
Over 200k book chapters abstractsL
Over 100k news articles and 20k+ product reviews abstracted
Non-textual Indexing: Multimedia, tables & graphs
Deep Domain Indexing: Chemical reaction, property data
Image processing involving sequence extraction using OCR technology, parse the documents and giving a structure to the final output.
We support publishers and content aggregators in the following ways through our A&I services
Indicative Abstracts
Describes what the document indicates in terms of topic and methodology, without providing the key content present in the article.
Informative Abstracts
Provide a condensed view of the entire content in the full-text document, culling out the key topics and concepts covered
Structured Abstracts
Created in a structured format with pre-defined headings that truly represent the way the full text is organized
Enhanced Abstracts
Picks out the key knowledge points that are helpful for decision making using domain expertise and inferences.
Video Transcript Abstracts
Extracting transcripts representing the theme of the video
Conceptual Indexing
Indexing key ideas/substances related to the novelty of the article/journal.
Image Indexing
Extracting keywords from captions that represent the core concept/theme of the image.
Controlled Indexing
Terms extracted from a controlled vocabulary and can either be actual keywords extracted from the caption or conceptually related terms assigned from the controlled vocabulary.
Multimedia Indexing
Providing terms for tables, graphs, video, etc
Chemical Structure Indexing
Indexing chemical structures from journal articles or patents
MC
MC Miner™ is a state-of-the-art text mining engine developed by the data scientists of Molecular Connections. The platform allows mining information from a range of unstructured data sources to create structured outputs which can be used to develop custom knowledgebases.
Key features:
- Can be also used as an indexing engine for developing an ontology
- APIs for interacting with external systems
- Supports concurrent access
- Inbuilt load balancer to manage concurrent access
- Custom MC Miner™ methods / algorithms
- Entity Extraction
- Topic Modelling
- Sentiment analysis
- Text Classification & Summarization
Application areas:
- Biology (Gene, Proteins, Species, Disease, Processes), Chemistry, Physics, Economics, Production Engineering
MC Parse A parsing engine whose key features are:
Non-XML parse:
A state of art non-XML parse for extracting text from PDF, doc, and other formats
Various PDF Structures (Dual column, Special Header elements)
Patent Offices/Full text Journals
Inconsistent Section Markers
Tables spanning across columns
XML Parse
XML parse consists of a library of parse based on xml formats of all major publishers, ncbi based formats like JATS, NLM Xml, PubMed, SciELO XML , etc. It can be customized for any new format in a very short span of time.
Areas of Application:
Research Articles
Patents
Reports
Manuscripts
MCAPS™
MCAPS™ (Molecular Connections Curation and Annotation Professional System) is a proprietary workflow system evolved through our expertise in life science curation.
Key features:
- Simplifies managing and exchanging heterogeneous data
- Facilitates guideline development & management for various curation and annotation projects
- Standard way to communicate data across projects and solves the data integration problem
- Makes report development easier
- Monitor project development in real-time
Areas of Application:
Management of indexing and text mining workflows
Data querying, analytics, and visualization
Product development and rapid prototyping
