NExTNet

Checkout NExTNet – “Biomedical Data Insight Discovery Tool”

NExTNet is a cloud-based platform that enables scientists to discover hidden connections between disparate data sources such as biomedical publications, drugs, genes, and pathways through its intuitive graphical user interface (GUI). It provides semantic search capabilities and no-code access to data beyond text, allowing for efficient communication and decision making.

• Product Category: Research
• Product Pricing Model: Freemium

• Biomedical Research Scientist
• Drug Discovery Analyst
• Bioinformatics Analyst
• Systems Biologist
• Clinical Researcher

For Biomedical Research Scientist

• Discovering hidden connections between genes and drugs for potential treatments of diseases
• Identifying new drug targets for a specific disease
• Analyzing gene expression patterns in different tissues to understand disease progression
• Visualizing complex biological pathways
• Comparing the efficacy of different drugs on cancer cells
• Visualizing protein structures and functions

• Drug discovery analysts can use NExTNet tool to identify potential drug targets for a specific disease by analyzing the relationships between genes, proteins, and pathways involved in that disease using its semantic search capabilities and generating hypotheses based on the data from biomedical publications and drugs.
• Scientists can use the platform to analyze the interactions between different drugs and their potential side effects on various diseases, allowing for more informed decision making during drug development.
• NExTNet tool can be used to identify new drug combinations that may have synergistic effects on a disease by analyzing the data from multiple sources such as genes, proteins, and pathways.
• Researchers can use the platform to analyze the potential of existing drugs for repurposing in treating other diseases or conditions.
• The tool can be used to identify new drug targets for rare diseases with limited research by analyzing gene-gene interactions and protein-protein interactions.

• Discovering hidden connections between diseases and drugs: As a Bioinformatics Analyst, one should use NExTNet tool to analyze the relationship between various diseases and their associated genes and drugs, allowing to identify potential drug targets for treatment options and generate hypotheses for further research.
• Identifying gene-gene interactions: Using NExTNet’s semantic search capabilities, one should explore the connections between different genes and their functions in a specific disease or condition to gain insights into the underlying mechanisms of the disease and develop new therapeutic strategies.
• Analyzing drug efficacy: one should use NExTNet to analyze the effectiveness of various drugs for a particular disease, comparing their potential side effects and benefits to identify the most suitable treatment options.
• Visualizing complex biological pathways: NExTNet’s graphical user interface would help create visual representations of complex biological pathways, allowing to better understand the interplay between different genes and proteins in a disease or condition.
• Collaborating with other researchers: NExTNet’s live collaboration features would enable to share findings and work with other scientists to develop new hypotheses and theories about disease mechanisms and potential treatments.

• Drug discovery: NExTNet can be used to analyze large amounts of biomedical literature and identify potential drug targets for a specific disease or condition by searching for genes, proteins, and pathways associated with it, and generating hypotheses based on the data from various sources such as publications and clinical trials.
• Gene expression analysis: NExTNet can be used to analyze gene expression data from microarray or RNA-seq experiments to identify differentially expressed genes and their functions in a particular tissue or disease state.
• Protein-protein interaction analysis: NExTNet can be used to identify potential interactions between proteins of interest and predict their role in disease development and progression.
• Pathway enrichment analysis: NExTNet can be used to identify the most relevant pathways involved in a specific disease or condition by analyzing gene expression data and protein-protein interaction networks.
• Network analysis: NExTNet can be used to analyze complex biological systems such as metabolic pathways, signaling pathways, and cellular processes to understand their interactions and functions.