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Marked drug-induced prolongation of the QT interval on the electrocardiogram is associated with Torsades de Pointes (TdP), a potentially life-threatening cardiac arrhythmia. Assessment of QT prolongation liability in the drug development process is required but is time and resource intensive. Current pre-clinical safety assessments use patch clamp analysis of the Human Ether-a-Go-Go (hERG) channel,...
With the advances in the next generation sequencing technology, huge amounts of data have been and get generated in biology. A bottleneck in dealing with such datasets lies in developing effective algorithms for extracting useful information from them. Algorithms for finding patterns in biological data pave the way for extracting crucial information from voluminous datasets. In this paper we focus...
Codon pair bias is the species-specific phenomenon that pairs of adjacent codons appear in genomes with frequencies different than would be predicted under an independence assumption, and thus is indicative of evolutionary selection. The synthetic attenuated virus engineering (SAVE) paradigm to design vaccines creates weak viruses by designing coding sequences that favor underrepresented codon pairs...
Biomedical semantic indexing refers to annotating biomedical citations with Medical Subject Headings, which is crucial for texting mining, information retrieval and other researches in the field of bioinformatics. The traditional methods ignore the relations among labels and need complicated feature engineering. In this paper, we present a novel model with a deep serial multi-task learning structure,...
Over the past few years, several approaches have been proposed to assist in the early diagnosis of Alzheimer's disease (AD) and its prodromal stage of mild cognitive impairment (MCI). For solving this high dimensional classification problem, the widely used algorithm remains to be Support Vector Machines (SVM). But due to the high variance of the data, the classification performance of SVM remains...
Typically, neuropsychological testing helps medical experts situate a given patient in continuum of the Alzheimer's disease (AD) spectrum, especially in the continuum between cognitively normal controls (CN) and the prodromal stage of mild cognitive impairment (MCI). As a well-known early symptom, some linguistic complexity changes of language have been associated with the progression of AD. Currently,...
Eldercare monitoring using non-wearable sensors is a candidate solution for improving care and reducing costs. Abnormal sensor patterns produced by certain resident behaviors could be linked to early signs of illness. We propose an unsupervised method for detecting abnormal behavior patterns based on a new context preserving representation of daily activities. A preliminary analysis of the method...
Drug Drug Interactions (DDIs) can cause harmful effect. Two shared tasks, DDIExtraction 2011 and DDIExtraction 2013, have been held to promote the implementation and comparative assessment of natural language processing techniques in the field of the pharmacovigilance domain. However, few model can meanwhile achieve state-of-the-art performance on both tasks. A major reason is the lack of representation...
To investigate cell spatial organization in complex biological dynamics, an individual-based model that represents cell motion in a deterministic way is proposed and then experimented on avascular tumor growth case. Cell motion remains a fundamental process in many complex biological dynamics such as morphogenesis or cell aggregation. Mathematical models are often used to represent cellular motility...
With the rapid adoption of smartphones and tablets, more and more remote medical diagnostic applications have mushroomed. Tongue Diagnosis (TD) is a kind of noninvasive diagnostic technique, which offers significant information for health conditions. However, it is rather tough to extract the tongue from a high-quality image, in which there is a definite large area of the tongue, to say nothing of...
In biomedical research, events revealing complex relations between entities play an important role. Event trigger identification is a crucial and prerequisite step in the pipeline process of biomedical event extraction. There exist two main problems in the previous work: (1) Traditional feature-based methods often rely on human ingenuity, which is a time-consuming process. Though most representation-based...
A clinical decision support system and its components may malfunction due to different reasons. The objective of this work is to develop computational methods that can help us to monitor the system and assure its proper operation by promptly detecting and analyzing changes in its behavior. We develop a new change-point detection method using the Multi-Process Dynamic Linear Model. The experiments...
Biologists synthesize research articles into coherent models—ideally, causal models, which predict how systems will respond to interventions. But it is challenging to derive causal models from articles alone, without primary data. To enable causal discovery using only literature, we built software for annotating empirical results in free text and computing valid explanations, expressed as causal graphs...
Pebble game rigidity analysis is a combinatorial method, implemented in our free web server KinariWeb, for extracting protein rigidity and flexibility information without performing costly molecular dynamics simulations. Due to the idiosynchrasies of the data in the Protein Data Bank (PDB), Kinari succeeds only on a fraction of the available files. Motivated by large scale applications, aiming at...
In recent years, there has been explosive growth in the amount of biomedical publications. In this paper, we propose a semantic framework that aims to automatically generate an ontology by extracting assertions and topics from multiple free-text scientific publications in PubMed. The pipeline approach for knowledge discovery and ontology generation in the proposed framework has been implemented on...
Beyond automated classification, supervised machine-learning models can be interpreted to find which features or combination of features distinguish sets of classes. Logistic Regression (LR) is an example of a model well-suited for human interpretation. Unfortunately, results from feature ranking with LR may not be reliable and reproducible for the same dataset. We demonstrate that stability and consistency...
Parkinson's disease is a debilitating and chronic disease of the nervous system. Traditional Chinese Medicine (TCM) is a new way for diagnosing Parkinson, and the data of Chinese Medicine for diagnosing Parkinson is a multi-label data set. Considering that the symptoms as the labels in Parkinson data set always have correlations with each other, we can facilitate the multi-label learning process by...
Early and accurate diagnosis of Alzheimer's disease is beneficial to both preserve daily functioning and test possible new treatments. However, current diagnosis depends on dozens of factors, including the family member, past medical problems, tests of memory, blood and urine tests, brain scans and even cerebrospinal fluid specimens. Among them, regular features (e.g., blood and urine tests, brain...
Current analysis of tumor proliferation, the most salient breast cancer prognostic biomarker, is limited to subjective mitosis counting by pathologists in localized regions of tissue images. This study presents the first data-driven integrative approach to characterize the severity of tumor growth and spread on a categorical and molecular level, utilizing multiple biologically salient deep learning...
From a biological standpoint, due to the special combination of complex symptoms, some type of complex diseases is difficult to be accurately diagnosed. Known as phenotypic overlap, these sets of disease-related symptoms reveal a common pathological and physiological mechanism. Researchers attempt to visualize the phenotypic relationships between different human diseases from the perspective of machine...
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