Brain age prediction using deep learning uncovers associated sequence variants
نویسندگان
چکیده
منابع مشابه
Toxicity Prediction using Deep Learning
Everyday we are exposed to various chemicals via food additives, cleaning and cosmetic products and medicines — and some of them might be toxic. However testing the toxicity of all existing compounds by biological experiments is neither financially nor logistically feasible. Therefore the government agencies NIH, EPA and FDA launched the Tox21 Data Challenge within the “Toxicology in the 21st C...
متن کاملDeepTox: Toxicity Prediction using Deep Learning
The Tox21 Data Challenge has been the largest effort of the scientific community to compare computational methods for toxicity prediction. This challenge comprised 12,000 environmental chemicals and drugs which were measured for 12 different toxic effects by specifically designed assays. We participated in this challenge to assess the performance of Deep Learning in computational toxicity predi...
متن کاملTraffic Prediction using a Deep Learning Paradigm
For many years intelligent transportation systems (ITS) have been collecting and processing huge amounts of data from numerous sensors to generate a ground truth of urban traffic. Such data has set the foundation of traffic theory, planning and simulation to create rule-based systems. It has also been used in many different studies in data-driven short-term traffic flow forecasting with promisi...
متن کاملRetrieval Term Prediction Using Deep Learning Methods
This paper presents methods to predict retrieval terms from relevant/surrounding words or descriptive texts in Japanese by using deep learning methods, which are implemented with stacked denoising autoencoders (SdA), as well as deep belief networks (DBN). To determine the effectiveness of using DBN and SdA for this task, we compare them with conventional machine learning methods, i.e., multi-la...
متن کاملDEEPre: sequence-based enzyme EC number prediction by deep learning
Motivation Annotation of enzyme function has a broad range of applications, such as metagenomics, industrial biotechnology, and diagnosis of enzyme deficiency-caused diseases. However, the time and resource required make it prohibitively expensive to experimentally determine the function of every enzyme. Therefore, computational enzyme function prediction has become increasingly important. In t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Nature Communications
سال: 2019
ISSN: 2041-1723
DOI: 10.1038/s41467-019-13163-9