Research

Deep-learning algorithm aims to accelerate protein engineering

7 days ago   |   By Phys

Proteins are the molecular machines of all living cells and have been exploited for use in many applications, including therapeutics and industrial catalysts. To overcome the limitations of naturally occurring proteins, protein engineering is used to improve protein characteristics such as stability and functionality. In a new study, researchers demonstrate a machine learning algorithm that accelerates the protein engineering process. The study is reported in the journal Nature Communications.
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Guest Editorial for Special Section on the 15 th International Conference on Intelligent Computing

7 days ago   |   By IEEE/ACM

The papers in this special section were presented at the Fifteenth International Conference on Intelligent Computing held on August 3-6, 2019, in Nanchang, Jiangxi Province, China.
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Predicting Human Intention-Behavior Through EEG Signal Analysis Using Multi-Scale CNN

7 days ago   |   By IEEE/ACM

At present, the application of Electroencephalogram signal classification to human intention-behavior prediction has become a hot topic in the brain computer interface research field. In recent studies, the introduction of convolutional neural networks has contributed to substantial improvements in the EEG signal classification performance. However, there is still a key challenge with the existing CNN-based EEG signal classification methods, the accuracy of them is not very satisfying. This is because most of the existing methods only utilize the feature maps in the last layer of CNN for...
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Subject-Independent Emotion Recognition of EEG Signals Based on Dynamic Empirical Convolutional Neural Network

7 days ago   |   By IEEE/ACM

Affective computing is one of the key technologies to achieve advanced brain-machine interfacing. It is increasingly concerning research orientation in the field of artificial intelligence. Emotion recognition is closely related to affective computing. Although emotion recognition based on electroencephalogram has attracted more and more attention at home and abroad, subject-independent emotion recognition still faces enormous challenges. We proposed a subject-independent emotion recognition algorithm based on dynamic empirical convolutional neural network in view of the challenges...
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A Multi-Scale Activity Transition Network for Data Translation in EEG Signals Decoding

7 days ago   |   By IEEE/ACM

Electroencephalogram is a non-invasive collection method for brain signals. It has broad prospects in brain-computer interface applications. Recent advances have shown the effectiveness of the widely used convolutional neural network in EEG decoding. However, some studies reveal that a slight disturbance to the inputs, e.g., data translation, can change CNN's outputs. Such instability is dangerous for EEG-based BCI applications because signals in practice are different from training data. In this study, we propose a multi-scale activity transition network to alleviate the influence of the...
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Advanced Machine-Learning Methods for Brain-Computer Interfacing

7 days ago   |   By IEEE/ACM

The brain-computer interface connects the brain and the external world through an information transmission channel by interpreting the physiological information of the brain during thinking activities. The effective classification of electroencephalogram signals is the key to improving the performance of the system. To improve the classification accuracy of EEG signals in the BCI system, the transfer learning algorithm and the improved Common Spatial Pattern algorithm are combined to construct a data classification model. Finally, the effectiveness of the proposed algorithm is verified...
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EEG-Based Brain-Computer Interfaces : A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications

7 days ago   |   By IEEE/ACM

Brain-Computer interfaces enhance the capability of human brain activities to interact with the environment. Recent advancements in technology and machine learning algorithms have increased interest in electroencephalographic -based BCI applications. EEG-based intelligent BCI systems can facilitate continuous monitoring of fluctuations in human cognitive states under monotonous tasks, which is both beneficial for people in need of healthcare support and general researchers in different domain areas. In this review, we survey the recent literature on EEG signal sensing technologies and...
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Guest Editorial: Advanced Machine-Learning Methods for Brain-Machine Interfacing or Brain-Computer Interfacing

7 days ago   |   By IEEE/ACM

The seven papers in this special section focus on advanced machine learning methods for brain machine interfacing. Particular emphasis is on novel theories and methods using transfer learning and deep learning proposed for Brain-Machine Interfacing or Brain-Computer Interfacing. Our purpose is to review the new progress and achievements on transfer learning, deep learning, and their applications in BMI or BCI in recent years.
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World Biotechnology Congress 2019

Hilaris Conferences is going to host its premier World Biotechnology Congress 2019 during October 01-02, 2019, Valencia, Spain. Biotechnology 2019 Congress aim to create a... Read more ...

World Biotechnology Congress 2019

Hilaris Conferences is going to host its premier World Biotechnology Congress 2019 during October 01-02, 2019, Valencia, Spain. Biotechnology 2019 Congress aim to create a... Read more ...

2nd International Conference on Tissue Science and Regenerative Medicine

This conference is designed for experts in academia and industries working in the tissue science and regenerative field, this conference will examine cutting-edge research in... Read more ...

Sr Scientist - Protein Sciences - Novartis / NIBR / GNF / San Diego...

High degree of self-motivation and attention to detail. Support the collection of analytical data. Present scientific and technical work.From Novartis - Sat, 16 Oct 2021... Read more ...

Benchmarking sequencing methods and tools that facilitate the study of...

Alternative cleavage and polyadenylation , an RNA processing event, occurs in over 70% of human protein-coding genes. APA results in mRNA transcripts with distinct 3′ ends... Read more ...

A global screening identifies chromatin-enriched RNA-binding proteins and...

Cellular RNA-binding proteins have multiple roles in post-transcriptional control, and some are shown to bind DNA. However, the global localization and the general... Read more ...

KrasG12D induces changes in chromatin territories that differentially impact...

Pancreatic ductal adenocarcinoma initiation is most frequently caused by Kras mutations. Read more ...

San Diego biotech veterans launch novel therapeutics firm targeting cancer...

Tentarix comes out of stealth mode, raises $50 million in venture funding led by Versant Ventures, Samsara BioCapital Read more ...

Genetic and process engineering strategies for enhanced recombinant...

The production of N-linked glycoproteins in genetically amenable bacterial hosts offers great potential for reduced cost, faster/simpler bioprocesses, greater customisation... Read more ...

Associate Director/Director Translational Research - Viracta Therapeutics...

5+ years of pharmaceutical or biotechnology industry experience in oncology/cancer immunotherapy. Viracta Therapeutics, a precision oncology company focused on...From Viracta... Read more ...

Long-Term Stable Reduction of Low-Density Lipoprotein in Nonhuman Primates...

Wang, L. et al. Molecular Therapy. 6, 2019-2029 (2021). Read more ...

Mitochondrial Targeted Meganuclease as a Platform to Eliminate Mutant mtDNA...

Zekonyte, U. et al. Nat Commun. 12, 3210 (2021). Read more ...

Scientists map brain circuit that drives activity in fertile females

Scientists have known for a century that female animals become more active just as they are about to ovulate, a behavior that evolved to enhance their chances of mating when... Read more ...