795 Decoding regulatory sequence across skin differentiation with deep learning
نویسندگان
چکیده
منابع مشابه
Near Maximum Likelihood Decoding with Deep Learning
A novel and efficient neural decoder algorithm is proposed. The proposed decoder is based on the neural Belief Propagation algorithm and the Automorphism Group. By combining neural belief propagation with permutations from the Automorphism Group we achieve near maximum likelihood performance for High Density Parity Check codes. Moreover, the proposed decoder significantly improves the decoding ...
متن کاملLearning Deep Temporal Representations for Brain Decoding
Functional magnetic resonance imaging produces high dimensional data, with a less then ideal number of labelled samples for brain decoding tasks (predicting brain states). In this study, we propose a new deep temporal convolutional neural network architecture with spatial pooling for brain decoding which aims to reduce dimensionality of feature space along with improved classification performan...
متن کاملFailure of skin-deep learning.
End-on view of the atomic model of the bacterial actinlike ParM protein double-helical fi lament, generated from an electron microscopic reconstruction. A bipolar spindle of antiparallel ParM fi laments pushes plasmids to the cell poles, constituting the simplest known apparatus for the segregation of genetic information. The loops on the outside of the 8to 9-nanometer-thick fi laments are invo...
متن کاملMelanoma detection with a deep learning model
Background: Skin cancer is one of the most common forms of cancer in the world and melanoma is the deadliest type of skin cancer. Both melanoma and melanocytic nevi begin in melanocytes (cells that produce melanin). However, melanocytic nevi are benign whereas melanoma is malignant. This work proposes a deep learning model for classification of these two lesions. Methods: In this analytic s...
متن کاملKey Regulatory Gene Expression in Erythroleukemia Differentiation
The characteristics of cellular and molecular mechanisms associated with cell proliferation and differentiation is important to understand malignancy. In this report we characterise a leukemic model, D5A1, to study the action of differentiation agent, cellular events and gene expression of the selected transcription factors. Cells induced with 4 mM hexamethylene bisacetamide (HMBA) caused signs...
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: Journal of Investigative Dermatology
سال: 2018
ISSN: 0022-202X
DOI: 10.1016/j.jid.2018.03.805