AIMC Topic: Computational Biology

Clear Filters Showing 2631 to 2640 of 4583 articles

Computational prediction of diagnosis and feature selection on mesothelioma patient health records.

PloS one
BACKGROUND: Mesothelioma is a lung cancer that kills thousands of people worldwide annually, especially those with exposure to asbestos. Diagnosis of mesothelioma in patients often requires time-consuming imaging techniques and biopsies. Machine lear...

Computational Prediction of Human Disease- Associated circRNAs Based on Manifold Regularization Learning Framework.

IEEE journal of biomedical and health informatics
The accumulating evidences regarding circular RNAs (circRNAs) indicate that they play crucial roles in a wide range of biological processes and participate in tumorigenesis and progression. The number of newly discovered circRNAs have increased drama...

An ontological foundation for ocular phenotypes and rare eye diseases.

Orphanet journal of rare diseases
BACKGROUND: The optical accessibility of the eye and technological advances in ophthalmic diagnostics have put ophthalmology at the forefront of data-driven medicine. The focus of this study is rare eye disorders, a group of conditions whose clinical...

Tuning the Performance of Synthetic Riboswitches using Machine Learning.

ACS synthetic biology
Riboswitch development for clinical, technological, and synthetic biology applications constantly seeks to optimize regulatory behavior. Here, we present a machine learning approach to improve the regulation of a tetracycline (tc)-dependent riboswitc...

DeepCDpred: Inter-residue distance and contact prediction for improved prediction of protein structure.

PloS one
Rapid, accurate prediction of protein structure from amino acid sequence would accelerate fields as diverse as drug discovery, synthetic biology and disease diagnosis. Massively improved prediction of protein structures has been driven by improving t...

funbarRF: DNA barcode-based fungal species prediction using multiclass Random Forest supervised learning model.

BMC genetics
BACKGROUND: Identification of unknown fungal species aids to the conservation of fungal diversity. As many fungal species cannot be cultured, morphological identification of those species is almost impossible. But, DNA barcoding technique can be empl...

Clinical intelligence: New machine learning techniques for predicting clinical drug response.

Computers in biology and medicine
Predicting the response, or sensitivity, of a clinical drug to a specific cancer type is an important research problem. By predicting the clinical drug response correctly, clinicians are able to understand patient-to-patient differences in drug sensi...

Extracting chemical-protein interactions from literature using sentence structure analysis and feature engineering.

Database : the journal of biological databases and curation
Information about the interactions between chemical compounds and proteins is indispensable for understanding the regulation of biological processes and the development of therapeutic drugs. Manually extracting such information from biomedical litera...

Combining relation extraction with function detection for BEL statement extraction.

Database : the journal of biological databases and curation
The BioCreative-V community proposed a challenging task of automatic extraction of causal relation network in Biological Expression Language (BEL) from the biomedical literature. Previous studies on this task largely used models induced from other re...

CRlncRC: a machine learning-based method for cancer-related long noncoding RNA identification using integrated features.

BMC medical genomics
BACKGROUND: Long noncoding RNAs (lncRNAs) are widely involved in the initiation and development of cancer. Although some computational methods have been proposed to identify cancer-related lncRNAs, there is still a demanding to improve the prediction...