Spinalnet: Deep neural network with gradual input
Deep neural networks (DNNs) have achieved the state-of-the-art (SOTA) performance in
numerous fields. However, DNNs need high computation times, and people always expect …
numerous fields. However, DNNs need high computation times, and people always expect …
Deep transformers and convolutional neural network in identifying DNA N6-methyladenine sites in cross-species genomes
As one of the most common post-transcriptional epigenetic modifications, N6-methyladenine
(6 mA), plays an essential role in various cellular processes and disease pathogenesis …
(6 mA), plays an essential role in various cellular processes and disease pathogenesis …
Bu-net: Brain tumor segmentation using modified u-net architecture
The semantic segmentation of a brain tumor is of paramount importance for its treatment and
prevention. Recently, researches have proposed various neural network-based …
prevention. Recently, researches have proposed various neural network-based …
Brainseg-net: Brain tumor mr image segmentation via enhanced encoder–decoder network
Efficient segmentation of Magnetic Resonance (MR) brain tumor images is of the utmost
value for the diagnosis of tumor region. In recent years, advancement in the field of neural …
value for the diagnosis of tumor region. In recent years, advancement in the field of neural …
CSatDTA: prediction of drug–target binding affinity using convolution model with self-attention
Drug discovery, which aids to identify potential novel treatments, entails a broad range of
fields of science, including chemistry, pharmacology, and biology. In the early stages of drug …
fields of science, including chemistry, pharmacology, and biology. In the early stages of drug …
[HTML][HTML] Heuristic analysis of genomic sequence processing models for high efficiency prediction: A statistical perspective
AR Durge, DD Shrimankar, AD Sawarkar - Current Genomics, 2022 - ncbi.nlm.nih.gov
Genome sequences indicate a wide variety of characteristics, which include species and
sub-species type, genotype, diseases, growth indicators, yield quality, etc. To analyze and …
sub-species type, genotype, diseases, growth indicators, yield quality, etc. To analyze and …
Deep6mAPred: A CNN and Bi-LSTM-based deep learning method for predicting DNA N6-methyladenosine sites across plant species
Abstract DNA N6-methyladenine (6mA) is a key DNA modification, which plays versatile
roles in the cellular processes, including regulation of gene expression, DNA repair, and …
roles in the cellular processes, including regulation of gene expression, DNA repair, and …
[HTML][HTML] DCNN-4mC: Densely connected neural network based N4-methylcytosine site prediction in multiple species
Abstract DNA N4-methylcytosine (4mC) being a significant genetic modification holds a
dominant role in controlling different biological functions, ie, DNA replication, DNA repair …
dominant role in controlling different biological functions, ie, DNA replication, DNA repair …
A review of methods for predicting DNA N6-methyladenine sites
K Han, J Wang, Y Wang, L Zhang, M Yu… - Briefings in …, 2023 - academic.oup.com
Abstract Deoxyribonucleic acid (DNA) N6-methyladenine plays a vital role in various
biological processes, and the accurate identification of its site can provide a more …
biological processes, and the accurate identification of its site can provide a more …
pcPromoter-CNN: a CNN-based prediction and classification of promoters
A promoter is a small region within the DNA structure that has an important role in initiating
transcription of a specific gene in the genome. Different types of promoters are recognized …
transcription of a specific gene in the genome. Different types of promoters are recognized …