Incorporating machine learning into established bioinformatics frameworks
N Auslander, AB Gussow, EV Koonin - International journal of molecular …, 2021 - mdpi.com
The exponential growth of biomedical data in recent years has urged the application of
numerous machine learning techniques to address emerging problems in biology and …
numerous machine learning techniques to address emerging problems in biology and …
Representation learning applications in biological sequence analysis
Although remarkable advances have been reported in high-throughput sequencing, the
ability to aptly analyze a substantial amount of rapidly generated biological …
ability to aptly analyze a substantial amount of rapidly generated biological …
A deep fusion matching network semantic reasoning model
As the vital technology of natural language understanding, sentence representation
reasoning technology mainly focuses on sentence representation methods and reasoning …
reasoning technology mainly focuses on sentence representation methods and reasoning …
A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information
Recently, language representation models have drawn a lot of attention in the natural
language processing field due to their remarkable results. Among them, bidirectional …
language processing field due to their remarkable results. Among them, bidirectional …
[PDF][PDF] The accuracy comparison among word2vec, glove, and fasttext towards convolution neural network (cnn) text classification
Feature extraction in the field of Text Processing or Natural Language Processing (NLP) has
its own challenges due to the characteristics of unstructured text. Thus, the selection of the …
its own challenges due to the characteristics of unstructured text. Thus, the selection of the …
BERT-Promoter: An improved sequence-based predictor of DNA promoter using BERT pre-trained model and SHAP feature selection
A promoter is a sequence of DNA that initializes the process of transcription and regulates
whenever and wherever genes are expressed in the organism. Because of its importance in …
whenever and wherever genes are expressed in the organism. Because of its importance in …
Msu-net: Multi-scale u-net for 2d medical image segmentation
R Su, D Zhang, J Liu, C Cheng - Frontiers in Genetics, 2021 - frontiersin.org
Aiming at the limitation of the convolution kernel with a fixed receptive field and unknown
prior to optimal network width in U-Net, multi-scale U-Net (MSU-Net) is proposed by us for …
prior to optimal network width in U-Net, multi-scale U-Net (MSU-Net) is proposed by us for …
DeepIPs: comprehensive assessment and computational identification of phosphorylation sites of SARS-CoV-2 infection using a deep learning-based approach
The rapid spread of SARS-CoV-2 infection around the globe has caused a massive health
and socioeconomic crisis. Identification of phosphorylation sites is an important step for …
and socioeconomic crisis. Identification of phosphorylation sites is an important step for …
DNN-DTIs: Improved drug-target interactions prediction using XGBoost feature selection and deep neural network
Abstract Analysis and prediction of drug-target interactions (DTIs) play an important role in
understanding drug mechanisms, as well as drug repositioning and design. Machine …
understanding drug mechanisms, as well as drug repositioning and design. Machine …
Challenges and advances towards the rational design of microalgal synthetic promoters in Chlamydomonas reinhardtii
Microalgae hold enormous potential to provide a safe and sustainable source of high-value
compounds, acting as carbon-fixing biofactories that could help to mitigate rapidly …
compounds, acting as carbon-fixing biofactories that could help to mitigate rapidly …