Genetics

Identifying COVID19 from Chest CT Images: A Deep Convolutional Neural Networks Based Approach.

Coronavirus Disease (COVID19) is a fast-spreading infectious disease that is currently causing a healthcare crisis around the world. Due to the current limitations of the reverse transcription-polymerase chain reaction (RT-PCR) based tests for detecting COVID19, recently radiology imaging based ideas have been proposed by various works. In this work, various Deep CNN based approaches are explored ...

A machine learning framework to trace tumor tissue-of-origin of 13 types of cancer based on DNA somatic mutation.

Carcinoma of unknown primary (CUP), defined as metastatic cancers with unknown cancer origin, occurs in 3-5 per 100 cancer patients in the United States. Heterogeneity and metastasis of cancer brings great difficulties to the follow-up diagnosis and treatment for CUP. To find the tissue-of-origin (TOO) of the CUP, multiple methods have been raised. However, the accuracies for computed tomography (...

Enhancing the interpretability of transcription factor binding site prediction using attention mechanism.

Transcription factors (TFs) regulate the gene expression of their target genes by binding to the regulatory sequences of target genes (e.g., promoters...

Design of Festival Sentiment Classifier Based on Social Network.

With the development of society, more and more attention has been paid to cultural festivals. In addition to the government's emphasis, the increasing...

Sequencing enabling design and learning in synthetic biology.

The ability to read and quantify nucleic acids such as DNA and RNA using sequencing technologies has revolutionized our understanding of life. With th...

Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.

Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. Predicting the overall survival of breast and ovar...

autoBioSeqpy: A Deep Learning Tool for the Classification of Biological Sequences.

Deep learning has proven to be a powerful method with applications in various fields including image, language, and biomedical data. Thanks to the lib...

Classifying Breast Cancer Subtypes Using Deep Neural Networks Based on Multi-Omics Data.

With the high prevalence of breast cancer, it is urgent to find out the intrinsic difference between various subtypes, so as to infer the underlying m...

A deep learning model to predict RNA-Seq expression of tumours from whole slide images.

Deep learning methods for digital pathology analysis are an effective way to address multiple clinical questions, from diagnosis to prediction of trea...

An Automatic Epilepsy Detection Method Based on Improved Inductive Transfer Learning.

Epilepsy is a chronic disease caused by sudden abnormal discharge of brain neurons, causing transient brain dysfunction. The seizures of epilepsy have...

Chances and challenges of machine learning-based disease classification in genetic association studies illustrated on age-related macular degeneration.

Imaging technology and machine learning algorithms for disease classification set the stage for high-throughput phenotyping and promising new avenues ...

Functional fine-mapping of noncoding risk variants in amyotrophic lateral sclerosis utilizing convolutional neural network.

Recent large-scale genome-wide association studies have identified common genetic variations that may contribute to the risk of amyotrophic lateral sc...

Machine Learning Approaches for Fracture Risk Assessment: A Comparative Analysis of Genomic and Phenotypic Data in 5130 Older Men.

The study aims were to develop fracture prediction models by using machine learning approaches and genomic data, as well as to identify the best model...

Machine-learning approach expands the repertoire of anti-CRISPR protein families.

The CRISPR-Cas are adaptive bacterial and archaeal immunity systems that have been harnessed for the development of powerful genome editing and engine...

Machine learning for predicting pathological complete response in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy.

For patients with locally advanced rectal cancer (LARC), achieving a pathological complete response (pCR) after neoadjuvant chemoradiotherapy (CRT) pr...

Patterns of 1,748 Unique Human Alloimmune Responses Seen by Simple Machine Learning Algorithms.

Allele specific antibody response against the polymorphic system of HLA is the allogeneic response marker determining the immunological risk for graft...

Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis.

We use deep transfer learning to quantify histopathological patterns across 17,355 hematoxylin and eosin-stained histopathology slide images from 28 c...

Pan-cancer image-based detection of clinically actionable genetic alterations.

Molecular alterations in cancer can cause phenotypic changes in tumor cells and their micro-environment. Routine histopathology tissue slides - which ...

Use Chou's 5-Step Rule to Predict DNA-Binding Proteins with Evolutionary Information.

The knowledge of DNA-binding proteins would help to understand the functions of proteins better in cellular biological processes. Research on the pred...

Combination of Estradiol with Leukemia Inhibitory Factor Stimulates Granulosa Cells Differentiation into Oocyte-Like Cells.

Previous studies have documented that cumulus granulosa cells (GCs) can trans-differentiation into different non-ovarian cells, showing their multipo...