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Ion channel classification through machine learning and protein language model embeddings

Author(s): Ghazikhani H; Butler G;

Ion channels are critical membrane proteins that regulate ion flux across cellular membranes, influencing numerous biological functions. The resource-intensive nature of traditional wet lab experiments for ion channel identification has led to an increasing emphasis on computational techniques. This study extends our previous work on protein language mode ...

Article GUID: 39572876


A protocol for trustworthy EEG decoding with neural networks

Author(s): Borra D; Magosso E; Ravanelli M;

Deep learning solutions have rapidly emerged for EEG decoding, achieving state-of-the-art performance on a variety of decoding tasks. Despite their high performance, existing solutions do not fully address the challenge posed by the introduction of many hyperparameters, defining data pre-processing, network architecture, network training, and data augment ...

Article GUID: 39549492


Modelling reindeer rut activity using on-animal acoustic recorders and machine learning

Author(s): Boucher AJ; Weladji RB; Holand Ø; Kumpula J;

For decades, researchers have employed sound to study the biology of wildlife, with the aim to better understand their ecology and behaviour. By utilizing on-animal recorders to capture audio from freely moving animals, scientists can decipher the vocalizations and glean insights into their behaviour and ecosystem dynamics through advanced signal processi ...

Article GUID: 38932958


Sentiment Classification Method Based on Blending of Emoticons and Short Texts

Author(s): Zou H; Xiang K;

With the development of Internet technology, short texts have gradually become the main medium for people to obtain information and communicate. Short text reduces the threshold of information production and reading by virtue of its short length, which is in line with the trend of fragmented reading in the context of the current fast-paced life. In additi ...

Article GUID: 35327909


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