Filter By:

  • Tissue-like electronic interfaces that form stable long-term interfaces in the brain will enable treatment of chronic neurological and psychiatric diseases.

    • Shaun R. Patel
    • Charles M. Lieber
  • Chien et al. reflect on lessons learned following the recent announcement that 31 papers from the Anversa laboratory on cardiac cell therapy are being retracted.

    • Kenneth R. Chien
    • Jonas Frisén
    • Irving L. Weissman
  • Brendan Frey and colleagues provide a personal overview of the machine learning field and in particular deep learning. They outline the technical challenges in applying machine learning to different types of biological and biomedical data and go on to discuss the challenges in implementing these approaches in the clinical realm, in drug discovery programs and within regulatory agencies.

    • Michael Wainberg
    • Daniele Merico
    • Brendan J Frey
  • Machine learning and natural language processing methods are applied to learn from PubMed searches and improve user experience.

    • Nicolas Fiorini
    • Robert Leaman
    • Zhiyong Lu
  • Recent developments in bioengineering promise the possibility of new diagnostic and treatment strategies, novel industrial processes, and innovative approaches to thorny problems in fields such as nutrition, agriculture, and biomanufacturing. As modern genetics has matured and developed technologies of increasing power, debates over risk assessments and proper applications of the technology, and over who should have decision-making power over such issues, have become more prominent. Recently, some scientists have advocated that ethicists “step out of the way,” whereas others have called for greater ethical scrutiny, or even for moratoria on some lines of research1,2. As a community, however, we must together determine the proper application of these powerful biological tools. This paper, a consensus statement of a group of interdisciplinary delegates drawn from the top biotech-producing countries of the world, offers a set of ethical principles to contribute to the ethical conversation about human cellular biotechnological research moving forward.

    • Paul Root Wolpe
    • Karen S Rommelfanger
  • Modern biological research increasingly relies on image data as a primary source of information in unraveling the cellular and molecular mechanisms of life. The quantity and complexity of the data generated by state-of-the-art microscopes preclude visual or manual analysis and require advanced computational methods to fully explore the wealth of information. In addition to making bioimage analysis more efficient, objective, and reproducible, the use of computers improves the accuracy and sensitivity of the analyses and helps to reveal subtleties that may be unnoticeable to the human eye. Many methods and software tools have already been developed to this end, but there is still a long way to go before biologists can blindly trust automated measurements. Here, we summarize the current state of the art in bioimage analysis and provide a perspective on likely future developments.

    • Erik Meijering
    • Anne E Carpenter
    • Jean-Christophe Olivo-Marin