IEEE/ACM transactions on computational biology and bioinformatics
Aug 6, 2021
With a variety of tumor subtypes, personalized treatments need to identify the subtype of a tumor as accurately as possible. The development of DNA microarrays provides an opportunity to predict tumor classification. One strategy is to use gene expre...
For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrai...
Biomedical materials (Bristol, England)
Aug 5, 2021
Nanomedicine has recently experienced unprecedented growth and development. However, the complexity of operations at the nanoscale introduces a layer of difficulty in the clinical translation of nanodrugs and biomedical nanotechnology. This problem i...
Non-negative matrix factorization (NMF) has become one of the most powerful methods for clustering and feature selection. However, the performance of the traditional NMF method severely degrades when the data contain noises and outliers or the manifo...
Background Patterns of metastasis in cancer are increasingly relevant to prognostication and treatment planning but have historically been documented by means of autopsy series. Purpose To show the feasibility of using natural language processing (NL...
A better understanding of the tumor immune microenvironment (TIME) could lead to accurate diagnosis, prognosis, and treatment stratification. Although molecular analyses at the tissue and/or single cell level could reveal the cellular status of the t...
Cancer tumor classification based on morphological characteristics alone has been shown to have serious limitations. Breast, lung, colorectal, thyroid, and ovarian are the most commonly diagnosed cancers among women. Precise classification of cancers...
Despite the existence of good catalogues of cancer genes, identifying the specific mutations of those genes that drive tumorigenesis across tumour types is still a largely unsolved problem. As a result, most mutations identified in cancer genes acros...
A cancer tumour consists of thousands of genetic mutations. Even after advancement in technology, the task of distinguishing genetic mutations, which act as driver for the growth of tumour with passengers (Neutral Genetic Mutations), is still being d...
The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and dri...
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