Jianxin Wang

Jianxin Wang
Central South University | CSU · School of Information Science and Engineering

Ph.D.

About

656
Publications
118,823
Reads
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12,133
Citations
Citations since 2017
364 Research Items
9600 Citations
201720182019202020212022202305001,0001,5002,0002,500
201720182019202020212022202305001,0001,5002,0002,500
201720182019202020212022202305001,0001,5002,0002,500
201720182019202020212022202305001,0001,5002,0002,500
Additional affiliations
January 2013 - present
Guangxi Normal University
September 2009 - present
Georgia State University
January 2002 - December 2012
Central South University

Publications

Publications (656)
Article
Accumulating evidences demonstrate that circular RNA (circRNA) plays an important role in human diseases. Identification of circRNA-disease associations can help for the diagnosis of human diseases, while the traditional method based on biological experiments is time-consuming. In order to address the limitation, a series of computational methods h...
Chapter
Chinese electronic medical records named entity recognition (NER) is a core task in medical knowledge mining, which is usually viewed as a sequence labeling problem. Recent works introduce the machine reading comprehension (MRC) framework into this task and extract named entities in a question-answering manner, resulting in state-of-the-art perform...
Chapter
International Classification of Disease (ICD) coding is to assign standard codes, which describe the state of a patient, to a clinical note. It is challenging given the complexity and the number of codes. The ICD taxonomy is hierarchically organized with several level codes (chapter, category, subcategory and its subdivision). However, most existin...
Article
Emerging evidence has proved that circular RNAs (circRNAs) are implicated in pathogenic processes. They are regarded as promising biomarkers for diagnosis due to covalently closed loop structures. As opposed to traditional experiments, computational approaches can identify circRNA-disease associations at a lower cost. Aggregating multi-source patho...
Article
Full-text available
Motivation: Oxford Nanopore sequencing has great potential and advantages in population-scale studies. Due to the cost of sequencing, the depth of whole-genome sequencing for per individual sample must be small. However, the existing SNP callers are aimed at high-coverage Nanopore sequencing reads. Detecting the SNP variants on low-coverage Nanopo...
Article
Circular RNAs (circRNAs) are reverse-spliced and covalently closed RNAs. Their interactions with RNA-binding proteins (RBPs) have multiple effects on the progress of many diseases. Some computational methods are proposed to identify RBP binding sites on circRNAs but suffer from insufficient accuracy, robustness and explanation. In this study, we fi...
Article
Drug discovery and drug repurposing often rely on the successful prediction of drug-target interactions (DTIs). Recent advances have shown great promise in applying deep learning to drug-target interaction prediction. One challenge in building deep learning-based models is to adequately represent drugs and proteins that encompass the fundamental lo...
Article
Problem Myocardial infarction (MI) is a classic cardiovascular disease (CVD) that requires prompt diagnosis. However, due to the complexity of its pathology, it is difficult for cardiologists to make an accurate diagnosis in a short period. Aim In the clinical, MI can be detected and located by the morphological changes on a 12-lead electrocardiog...
Article
Full-text available
Background: The sinoatrial node (SAN) functions as the pacemaker of the heart, initiating rhythmic heartbeats. Despite its importance, the SAN is one of the most poorly understood cardiac entities because of its small size and complex composition and function. The Hippo signaling pathway is a molecular signaling pathway fundamental to heart develo...
Article
In healthcare, Intensive Care Unit (ICU) bed management is a necessary task because of the limited budget and resources. Predicting the remaining Length of Stay (LoS) in ICU and mortality can assist clinicians in managing ICU beds efficiently. This study proposes a deep learning method based on several successive Temporal Dilated Separable Convolut...
Article
Brain penumbra is a critical condition that is closely related to stroke. Thus, there is high demand for fast and accurate segmentation of penumbra tissue in magnetic resonance images. However, most convolutional neural networks (CNNs) focus on learning contextual semantic information from two-dimensional imaging slides, ignoring the spatiotemporal...
Article
Neural crest cells (NCCs) are multipotent stem cells that can differentiate into multiple cell types, including the osteoblasts and chondrocytes, and constitute most of the craniofacial skeleton. Here, we show through in vitro and in vivo studies that the transcriptional regulators Yap and Taz have redundant functions as key determinants of the spe...
Article
Pathogens producing β-lactamase pose a great challenge to antibiotic-resistant infection treatment; thus, it is urgent to discover novel β-lactamase inhibitors for drug development. Conventional high-throughput screening is very costly, and structure-based virtual screening is limited with mechanisms. In this study, we construct a novel multichanne...
Preprint
A fundamental challenge in deep metric learning is the generalization capability of the feature embedding network model since the embedding network learned on training classes need to be evaluated on new test classes. To address this challenge, in this paper, we introduce a new method called coded residual transform (CRT) for deep metric learning t...
Article
Modern data centers often host multiple applications with diverse network demands. To provide fair bandwidth allocation to several thousand traversing flows, Approximate Fair Queueing (AFQ) utilizes multiple priority queues in switch to approximate ideal fair queueing. However, due to limited number of queues in programmable switches, AFQ easily ex...
Preprint
High sequencing errors have impeded the application of long noisy reads for diploid genome assembly. Most existing assemblers failed to distinguish heterozygotes from high sequencing errors in long noisy reads and generate collapsed assemblies with lots of haplotype switches. Here, we present PECAT, a phased error correction and assembly tool for r...
Article
In the original paper [1], there are two errors on page 5.The rules in the algorithm are not sufficient since we omitted one rule during publication. The following rule should be added to the paper.Rule 3: If P1 = (u, v) and P2 = (x, y) are two maximal leaf-paths both with two vertices in T, where u and x are leaves in T and (v, y) ∈ E(G), we remov...
Article
Full-text available
In modern data centers, the congestion-aware load balancing makes rerouting decisions according to the traffic load. However, it is difficult to accurately obtain network load status using limited congestion information. Recently, In-band Network Telemetry (INT) has been embedded in the latest merchant silicones to support information collection of...
Article
Full-text available
For a graph search algorithm, the end vertex problem is concerned with which vertices of a graph can be the last visited by this algorithm. We characterize all maximum cardinality searches on chordal graphs and derive from this characterization a polynomial-time algorithm for the end vertex problem of maximum cardinality searches on chordal graphs....
Article
Motivation Due to cancer heterogeneity, the therapeutic effect may not be the same when a cohort of patients of the same cancer type receive the same treatment. The anticancer drug response prediction may help develop personalized therapy regimens to increase survival and reduce patients' expenses. Recently graph neural network-based methods have a...
Article
As a frontier field of individualized therapy, microRNA (miRNA) pharmacogenomics facilitates the understanding of different individual responses to certain drugs and provides a reasonable reference for clinical treatment. However, the known drug resistance-associated miRNAs are not yet sufficient to support precision medicine. Although existing met...
Article
The third-generation sequencing technology has advanced genome analysis with long read length, but the reads need error correction due to the high error rate. Error correction is a time-consuming process especially when the sequencing coverage is high. Generally, for a pair of overlapping reads A and B, the existing error correction methods perform...
Preprint
Human leukocyte antigen (HLA) is an important molecule family in the field of human immunity, which recognizes foreign threats and triggers immune responses by presenting peptides to T cells. In recent years, the synthesis of tumor vaccines to induce specific immune responses has become the forefront of cancer treatment. Computationally modeling th...
Article
Most providers of video streaming are interested in improving quality of user experience across various wireless network circumstances. Many buffer-based ABR algorithms have been proposed to adjust the bitrate according to the buffer occupancy at the client player. Though keeping the buffer occupancy stable, such ABR algorithms cannot provide satis...
Article
ABSTRACT Single-cell RNA sequencing (scRNA-seq) can present cellular heterogeneity at higher resolution when measuring the gene expression in an individual cell. However, there are still some computational problems in scRNA-seq data, including high dimensionality, high sparseness, and high noise. To solve them, dimensionality reduction is essential...
Preprint
Full-text available
Cervical abnormal cell detection is a challenging task as the morphological differences between abnormal cells and normal cells are usually subtle. To determine whether a cervical cell is normal or abnormal, cytopathologists always take surrounding cells as references and make careful comparison to identify its abnormality. To mimic these clinical...
Article
Motivation: Identifying drug-target interactions is a crucial step for drug discovery and design. Traditional biochemical experiments are credible to accurately validate drug-target interactions. However, they are also extremely laborious, time-consuming, and expensive. With the collection of more validated biomedical data and the advancement of c...
Article
Full-text available
In this paper, we study the following pattern search problem: Given a pair of point sets A and B in fixed dimensional space \(\mathbb {R}^d\), with \(|B| = n,|A| = m\) and \(n \ge m\), the pattern search problem is to find the translations \(\mathcal {T}\)’s of A such that each of the identified translations induces a matching between \(\mathcal {T...
Conference Paper
The k-means problem is an extensively studied unsupervised learning problem with various applications in decision making and data mining. In this paper, we propose a fast and practical local search algorithm for the k-means problem. Our method reduces the search space of swap pairs from O(nk) to O(k^2), and applies random mutations to find potentia...
Article
In recent years, deep learning as a state-of-the-art machine learning technique has made great success in histopathological image classification. However, most of deep learning approaches rely heavily on the substantial task-specific annotations, which require experienced pathologists’ manual labelling. As a result, they are laborious and time-cons...
Article
Alzheimer's disease (AD) is the most common neurodegenerative disease. More and more evidence show that DNA methylation is closely related to the pathological mechanism of AD. Many AD-associated differentially methylated genes, regions and CpG sites have been identified in recent research, which will have great potential in clinical research. Howev...
Preprint
Full-text available
Motivation Circular RNAs (circRNAs) with varied biological activities are implicated in pathogenic processes, according to new findings. They are regarded as promising biomarkers for the diagnosis and prognosis due to their structural features. Computational approaches, as opposed to traditional experiments, can identify the circRNA-disease connect...
Article
The prediction of drug-target affinities (DTAs) is substantial in drug development. Recently, deep learning has made good progress in the prediction of DTAs. Although relatively effective, due to the black-box nature of deep learning, these models are less biologically interpretable. In this study, we proposed a deep learning-based model, named Att...
Preprint
Accurately detecting Alzheimer's disease (AD) and predicting mini-mental state examination (MMSE) score are important tasks in elderly health by magnetic resonance imaging (MRI). Most of the previous methods on these two tasks are based on single-task learning and rarely consider the correlation between them. Since the MMSE score, which is an impor...
Article
The emerging latency-sensitive services such as smart grid and tactile internet require deterministic network performance including deterministic end-to-end latency, latency jitter and bounded packet loss rate. To empower standard Ethernet with such capability, we provide a deterministic forwarding system named DLCC with end-to-end congestion contr...
Article
Full-text available
The Maximum satisfiability problem (MaxSAT) is a fundamental NP-hard problem which has significant applications in many areas. Based on refined observations, we derive a branching algorithm of running time O∗(1.2989m)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy...
Article
The lower-bounded k-median problem plays a key role in many applications related to privacy protection, which requires that the amount of assigned client to each facility should not be less than the requirement. Unfortunately, the lower-bounded clustering problem remains elusive under the widely studied k-median objective. Within this paper, we con...
Article
Accurate prediction of pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) is essential for clinical precision treatment. However, the existing methods of predicting pCR in esophageal cancer are based on the single stage data, which limits the performance of these methods. Effective fusion of the longitudinal data has th...
Article
Model selection for deep learning algorithms is an extremely important step in the process of extracting knowledge from limited data, especially in biomedical data. The common approach is to adopt cross-validation techniques to randomly divide a small subset of the training set as the validation data for parameter tuning and model selection. Howeve...
Article
Determining drug indications is a critical part of the drug development process. However, traditional drug discovery is expensive and time-consuming. Drug repositioning aims to find potential indications for existing drugs, which is considered as an important alternative to the traditional drug discovery. In this article, we propose a multi-view le...
Article
The video streaming system employs adaptive bitrate (ABR) algorithms to optimize user’s quality of experience (QoE). However, it is hard for ABR algorithms to choose the right bitrate consistently under highly dynamic bandwidth fluctuations in wild Internet. In this paper, we propose a building block on the client-side named Opportunistic Chunk Rep...
Preprint
Full-text available
It has been reported recently that DNA 5-methylcytosine (5mC) in CpG contexts can be detected using PacBio circular consensus sequencing (CCS). However, the accuracy and robustness of computational methods using long CCS reads still need to be improved. In this study, we present a deep learning method, ccsmeth, to detect DNA 5mCpGs from PacBio CCS...
Article
Full-text available
Objectives: We aimed to develop deep learning models using longitudinal chest X-rays (CXRs) and clinical data to predict in-hospital mortality of COVID-19 patients in the intensive care unit (ICU). Methods: Six hundred fifty-four patients (212 deceased, 442 alive, 5645 total CXRs) were identified across two institutions. Imaging and clinical dat...
Article
Motivation Many studies have shown that microRNAs (miRNAs) play a key role in human diseases. Meanwhile, traditional experimental methods for miRNA-disease association identification are extremely costly, time-consuming, and challenging. Therefore, many computational methods have been developed to predict potential associations between miRNAs and d...
Article
Single cell RNA sequencing (scRNA-seq) provides a powerful approach for profiling transcriptomes at single cell resolution. Currently, existing single cell clustering methods are exclusively based on gene-level expression data, without considering alternative splicing information. We therefore hypothesize that adding information about alternative s...
Article
Multi-Path TCP (MPTCP) shows its unique advantages over single-path TCP thanks to its aggregate throughput from multiple paths, balancing efficiency and fairness over multipath transmission. However, MPTCP senders should tackle the friendliness issue carefully when sharing the same bottleneck with single-path TCP. Unfortunately, existing shared bot...
Article
Motivation: Alzheimer's disease (AD) is a complex brain disorder with risk genes incompletely identified. The candidate genes are dominantly obtained by computational approaches. In order to obtain biological insights of candidate genes or screen genes for experimental testing, it is essential to assess their relevance to AD. A platform that integ...
Article
Alzheimer's disease (AD) has a strong genetic predisposition. However, its risk genes remain incompletely identified. We developed an Alzheimer's brain gene network-based approach to predict AD-associated genes by leveraging the functional pattern of known AD-associated genes. Our constructed network outperformed existing networks in predicting AD...
Article
The accurate prediction of isocitrate dehydrogenase (IDH) mutation and glioma segmentation are important tasks for computer-aided diagnosis using preoperative multimodal magnetic resonance imaging (MRI). The two tasks are ongoing challenges due to the significant inter-tumor and intra-tumor heterogeneity. The existing methods to address them are mo...
Article
Full-text available
Dynamic adaptive streaming over HTTP (DASH) has been widely deployed to provide various video services in the Internet. However, the HTTP/1.1 or HTTP/2 utilized by the DASH system cannot ensure high quality of user experience in highly dynamic network scenarios. Specifically, when the clients fetch the video chunks from servers, it is well known th...
Article
Video traffic has experienced an exponential increase in current years due to the growing ubiquity of mobile equipment and the constant network improvement. To deliver video in high quality across various network conditions, adaptive bitrate (ABR) algorithms dynamically select bitrate for each chunk according to perceived network rate and buffer oc...
Article
Most commercial players adopt adaptive bitrate (ABR) algorithms to dynamically decide each chunk's bitrate based on the perceived network bandwidth and buffer occupancy. However, current ABR algorithms are agnostic of audio bitrate selection since they deem it has negligible influence on video bitrate selection due to small size of audio chunks. Ne...
Article
Identifying heavy flows is essential for network management. However, it is challenging to detect heavy flow quickly and accurately under the highly dynamic traffic and rapid growth of network capacity. Existing heavy flow detection schemes can make a trade-off in efficiency, accuracy and speed. However, these schemes still require memory large eno...
Article
Since most flows are short-lived in data center networks, fast convergence becomes very important to help the short flows effectively utilize high bandwidth. Though current explicit feedback-based transport control protocols (TCPs) provide fast convergence via fine-grained congestion information from customized switches, they unavoidably incur larg...
Article
Lip reading can help people with speech disorders to communicate with others and provide them with a new channel to interact with the world. In this paper, we design and implement HearMe , an accurate and real-time lip-reading system built on commercial RFID devices. HearMe can be used to accurately recognize different words in a pre-defined voca...
Article
Datacenter networks provide large bisection bandwidth by load balancing traffic over rich parallel paths in multi-rooted tree topologies. Nevertheless, production datacenters operate under various path diversities caused by traffic dynamics, hardware failures and heterogeneous switching equipment. Therefore, the load balancing schemes in data cente...
Article
Gesture recognition based on radio frequency identification (RFID) has attracted much research attention in recent years. Most existing RFID-based gesture recognition approaches use signal profile matching to distinguish different gestures, which incur large recognition latency and fail to support real-time applications. In this paper, we design an...
Article
Performing accurate sensing in diverse environments is a challenging issue in wireless sensing technologies. Existing solutions usually require collecting a large number of samples to train a classifier for every environment, or further assume similar sample distribution between different environments such that a model trained in one environment ca...
Article
Existing reactive or proactive congestion control protocols are hard to simultaneously achieve ultra-low latency and high link utilization across all workloads ranging from delay-sensitive flows to bandwidth-hungry ones in datacenter networks. We present an Anti-ECN (Explicit Congestion Notification) Marking Receiver-driven Transport protocol calle...
Article
The diagnosis of mild cognitive impairment (MCI), which is an early stage of Alzheimer’s disease (AD), has great clinical significance. Medical imaging and gene sequencing technologies have provided sufficient multimodality data for MCI diagnostic studies. However, how to effectively extract the rich representations from multimodality data remains...
Article
Distributed key-value stores provide the Multiget API, where many key-value operations are batched together, to meet the parallel requirement of applications. Correspondingly, reducing the latency of Multigets is crucial for the responsiveness of the distributed key-value stores. The latency of a Multiget depends on both which replica server its ke...
Article
In distributed key-value stores, multiple replica servers are always available for each key-value access operation when the eventual consistency model is employed. Accordingly, the completion times of the key-value access operations generated by an end-user request at different servers may be of great difference, especially when the replica servers...
Article
The three-dimensional deployment of Unmanned Aerial Vehicles (UAVs) has attracted extensive attention, especially for the Internet of Vehicles (IoV) in an emergency or to help the overloaded edge servers in traffic peaks. However, most existing works assume a two-dimensional road to simplify the design and modeling, while ignoring the interchange b...
Article
In recent years, receiver-driven transport protocols have been proposed to use proactive congestion control to meet the stringent latency requirements of large-scale applications in data center. However, the receiver-driven proposals face the challenges brought by network dynamic. Firstly, when the bursty flows start, the aggressive and blind line-...
Article
Adaptive bitrate (ABR) algorithms are employed for delivering media content across wireless networks. Current ABR schemes only focus on video bitrate adaptation, considering that audio content encoding has negligible impact on streaming quality, due to its smaller size. However, many commercial platforms use high-quality audio which is significant...
Article
Investigating differentially methylated regions (DMRs) presented in different tissues or cell types can help to reveal the mechanisms behind the tissue-specific gene expression. The identified tissue-/disease-specific DMRs also can be used as feature markers for spotting the tissues-of-origins of cell-free DNA (cfDNA) in noninvasive diagnosis. In r...
Article
Full-text available
Repeats are prevalent in the genomes of all bacteria, plants and animals, and they cover nearly half of the Human genome, which play indispensable roles in the evolution, inheritance, variation and genomic instability, and serve as substrates for chromosomal rearrangements that include disease-causing deletions, inversions, and translocations. Comp...
Chapter
Single-cell RNA-seq (scRNA-seq) data has provided a higher resolution of cellular heterogeneity. However, scRNA-seq data also brings some computational challenges for its high-dimension, high-noise, and high-sparseness. The dimension reduction is a crucial way to denoise and greatly reduce the computational complexity by representing the original d...
Chapter
Viral infectious diseases are threatening human health and global security by rapid transmission and severe fatalities. The receptor-binding is the first step of viral infection. Identifying hidden virus-receptor interactions opens new perspectives to understand the virus-receptor interaction mechanisms, and further help develop an economical and e...
Article
The side effects of drugs present growing concern attention in the healthcare system. Accurately identifying the side effects of drugs is very important for drug development and risk assessment. Some computational models have been developed to predict the potential side effects of drugs and provided satisfactory performance. However, most existing...
Article
Motivation Identifying drug–target interactions (DTIs) is a crucial step in drug repurposing and drug discovery. Accurately identifying DTIs in silico can significantly shorten development time and reduce costs. Recently, many sequence-based methods are proposed for DTI prediction and improve performance by introducing the attention mechanism. Howe...
Article
Full-text available
In plants, cytosine DNA methylations (5mCs) can happen in three sequence contexts as CpG, CHG, and CHH (where H = A, C, or T), which play different roles in the regulation of biological processes. Although long Nanopore reads are advantageous in the detection of 5mCs comparing to short-read bisulfite sequencing, existing methods can only detect 5mC...
Article
Long-read sequencing technology enables significant progress in de novo genome assembly. However, the high error rate and the wide error distribution of raw reads result in a large number of errors in the assembly. Polishing is a procedure to fix errors in the draft assembly and improve the reliability of genomic analysis. However, existing methods...