A new Web application can help researchers analyze the extensive NC1-60 cell line database, compiled by the U.S. National Cancer Institute and used by organizations to develop cancer therapies. The application, known as CellMiner, allows for “rapid data retrieval of transcripts for 22,379 genes and 360 microRNAs along with activity reports for 20,503 chemical compounds” including 102 drugs approved by the Federal Drug Administration, according to an abstract posted by the American Association for Cancer Research. “Data queries for potential relationships among parameters can be conducted in an iterative manner specific to user interests and expertise.” Among the potential benefits, according to that abstract, is the ability of researchers with relatively little bioinformatics experience—that’s the use of statistics and computer science within the context of molecular biology—to perform complex analyses using the NC1-60 database. CellMiner users can visit the database Website for access to a number of information streams, including NCI-60 Analysis Tools for automation of several commonly-done analyses, dataset metadata, queries for genomic and drug data, cell line metadata, and mutation data (a list of mutations found in 24 known human cancer genes). Big Data and data-analytics tools have become a vital tool in many areas of medical research. IBM, for example, has been exploring ways to incorporate its Watson platform as a sort of B.I.-as-a-service for healthcare providers, with the potential to help diagnose diseases and provide diagnostic and treatment options. Meanwhile, the Massachusetts Institute of Technology (MIT) and Intel are collaborating on a new Intel Science and Technology (ISTC) for Big Data at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), which will partially focus on how analytics can help tailor better medical treatments. The challenge with any of this, of course, is designing tool sets equal to the massive amounts of information at hand. The Association for Information and Image Management (AIIM), a nonprofit organization that provides resources and education to information professionals, recently surveyed 403 of its members and found that some 55 percent of organizations lack either search or analytics capabilities. When it comes to medical research, tools like CellMiner could go a long way to meeting that challenge. Image: Juan Gaertner/Shutterstock.com CellMiner Data Analytics App Could Help With Cancer Research
A new Web application can help researchers analyze the extensive NC1-60 cell line database, compiled by the U.S. National Cancer Institute and used by organizations to develop cancer therapies. The application, known as CellMiner, allows for “rapid data retrieval of transcripts for 22,379 genes and 360 microRNAs along with activity reports for 20,503 chemical compounds” including 102 drugs approved by the Federal Drug Administration, according to an abstract posted by the American Association for Cancer Research. “Data queries for potential relationships among parameters can be conducted in an iterative manner specific to user interests and expertise.” Among the potential benefits, according to that abstract, is the ability of researchers with relatively little bioinformatics experience—that’s the use of statistics and computer science within the context of molecular biology—to perform complex analyses using the NC1-60 database. CellMiner users can visit the database Website for access to a number of information streams, including NCI-60 Analysis Tools for automation of several commonly-done analyses, dataset metadata, queries for genomic and drug data, cell line metadata, and mutation data (a list of mutations found in 24 known human cancer genes). Big Data and data-analytics tools have become a vital tool in many areas of medical research. IBM, for example, has been exploring ways to incorporate its Watson platform as a sort of B.I.-as-a-service for healthcare providers, with the potential to help diagnose diseases and provide diagnostic and treatment options. Meanwhile, the Massachusetts Institute of Technology (MIT) and Intel are collaborating on a new Intel Science and Technology (ISTC) for Big Data at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), which will partially focus on how analytics can help tailor better medical treatments. The challenge with any of this, of course, is designing tool sets equal to the massive amounts of information at hand. The Association for Information and Image Management (AIIM), a nonprofit organization that provides resources and education to information professionals, recently surveyed 403 of its members and found that some 55 percent of organizations lack either search or analytics capabilities. When it comes to medical research, tools like CellMiner could go a long way to meeting that challenge. Image: Juan Gaertner/Shutterstock.com