Given that the biological processes governing the oncogenesis of pancreatic cancers could present useful therapeutic targets, there is a pressing need to molecularly distinguish between different clinically relevant pancreatic cancer subtypes. To add...
Machine learning techniques have been previously applied for classification of tumors based largely on morphological features of tumor cells recognized in H&E images. Here, we tested the possibility of using numeric data acquired from software-based ...
BACKGROUND: With recent advances in high-throughput technologies, matrix factorization techniques are increasingly being utilized for mapping quantitative omics profiling matrix data into low-dimensional embedding space, in the hope of uncovering ins...
Environmental pollution (Barking, Essex : 1987)
Dec 4, 2019
Cypermethrin is a frequently used insecticide in agriculture and households but its chronic and molecular effects are poorly known are . Here we describe effects of sublethal cypermethrin exposure on the global transcriptome in the brain of honey bee...
"miRNA colorectal cancer" (https://mirna-coadread.omics.si/) is a freely available web application for studying microRNA and mRNA expression and their correlation in colorectal cancer. To the best of our knowledge, "miRNA colorectal cancer" has the l...
BACKGROUND: Long-chain non-coding RNA (lncRNA) is closely related to many biological activities. Since its sequence structure is similar to that of messenger RNA (mRNA), it is difficult to distinguish between the two based only on sequence biometrics...
Microinjection into single cells in brain tissue is a powerful technique to study and manipulate neural stem cells. However, such microinjection requires expertise and is a low-throughput process. We developed the "Autoinjector", a robot that utilize...
Analytical cellular pathology (Amsterdam)
Aug 4, 2019
Human hepatocellular carcinoma (HCC) is the most common and recurrent type of primary adult liver cancer without any effective therapy. Plant-derived compounds acting as anticancer agents can induce apoptosis by targeting several signaling pathways. ...
BACKGROUND: Unsupervised machine learning methods (deep learning) have shown their usefulness with noisy single cell mRNA-sequencing data (scRNA-seq), where the models generalize well, despite the zero-inflation of the data. A class of neural network...
Alternative polyadenylation (APA) is a major driver of transcriptome diversity in human cells. Here, we use deep learning to predict APA from DNA sequence alone. We trained our model (APARENT, APA REgression NeT) on isoform expression data from over ...