Collaborating Authors

2017: A Breakthrough Year in Genomics


Evelyn Villareal was born with spinal muscular atrophy type 1 (SMA1), a genetic disease that gradually paralyzes babies. The diagnosis was heartbreaking for her parents, who lost their first daughter to the condition when she was just 15 months old. Most affected children rarely live past two.

Machine Learning in Genomics โ€“ Current Efforts and Future Applications Emerj


Genomics is a branch of molecular biology focused on studying all aspects of a genome, or the complete set of genes within a particular organism. Today, machine learning is playing an integral role in the evolution of the field of genomics. We set out in this article to examine the applications of machine learning in genomics to help business leaders understand current and emerging trends within the field. Before diving into present applications, we'll begin with background facts and terminology about genomics and precision medicine, and a quick summary of the findings of our research on this topic: The ability to sequence DNA provides researchers with the ability to "read" the genetic blueprint that directs all the activities of a living organism. To provide context, the central dogma of biology is summarized as the pathway from DNA to RNA to Protein.

Genome sequencing can provide the key to cancer prevention


A genome is the body's instruction manual. It's made of DNA and there is a copy in almost every cell. Through genome sequencing and genomics, clinicians can better understand how cancer cells might evolve and what treatments will be most responsive, known as precision and personalised medicine. Furthermore, genomics combined with technologies such as machine-learning and artificial intelligence (AI) has huge, as yet untapped, potential for determining a healthy person's future risk of cancer. To sequence the first genome cost $3 billion and took 13 years.

Looking to the Future


Innovations in cancer research through interdisciplinary team science approaches will help shape the future of patient care. Integration and mining of health care data from various sources will allow researchers to gain more insights into cancer biology and thereby improve patient outcomes. Cutting-edge technologies that fuel the full spectrum of cancer science from bench to bedside will accelerate the pace at which we increase our understanding of cancer biology while transforming the future of clinical practice. This is an exciting era of cancer research. Approval of novel therapeutics, coupled with an increasing public awareness of cancer prevention and early detection, has led to dramatic reductions in overall cancer mortality rates for all Americans.

6 expert essays on the future of biotech


What exactly is biotechnology, and how could it change our approach to human health? As the age of big data transforms the potential of this emerging field, members of the World Economic Forum's Global Future Council on Biotechnology tell you everything you need to know. What if your doctor could predict your heart attack before you had it โ€“ and prevent it? Or what if we could cure a child's cancer by exploiting the bacteria in their gut? These types of biotechnology solutions aimed at improving human health are already being explored. As more and more data (so called "big data") is available across disparate domains such as electronic health records, genomics, metabolomics, and even life-style information, further insights and opportunities for biotechnology will become apparent. However, to achieve the maximal potential both technical and ethical issues will need to be addressed. As we look to the future, let's first revisit previous examples of where combining data with scientific understanding has led to new health solutions. Biotechnology is a rapidly changing field that continues to transform both in scope and impact. Karl Ereky first coined the term biotechnology in 1919.