A computational method for prediction of matrix proteins in endogenous retroviruses.

Human endogenous retroviruses (HERVs) encode active retroviral proteins, which may be involved in the progression of cancer and other diseases. Matrix protein (MA), in group-specific antigen genes (gag) of retroviruses, is associated with the virus envelope glycoproteins in most mammalian retroviruses and may be involved in virus particle assembly, transport and budding. However, the amount of annotated MAs in ERVs is still at a low level so far.

A computational model for predicting transmembrane regions of retroviruses.

Transmembrane region (TR) is a conserved region of transmembrane (TM) subunit in envelope (env) glycoprotein of retrovirus. Evidences have shown that TR is responsible for anchoring the env glycoprotein on the lipid bilayer and substitution of the TR for a covalently linked lipid anchor abrogates fusion. However, universal software could not achieve sufficient accuracy as TM in env also has several motifs such as signal peptide, fusion peptide and immunosuppressive domain composed largely of hydrophobic residues.

A novel method for in silico identification of regulatory SNPs in human genome.

Regulatory single nucleotide polymorphisms (rSNPs), kind of functional noncoding genetic variants, can affect gene expression in a regulatory way, and they are thought to be associated with increased susceptibilities to complex diseases. Here a novel computational approach to identify potential rSNPs is presented. Different from most other rSNPs finding methods which based on hypothesis that SNPs causing large allele-specific changes in transcription factor binding affinities are more likely to play regulatory functions, we use a set of documented experimentally verified rSNPs and nonfunctional background SNPs to train classifiers, so the discriminating features are found.

An Energy Saving System for a Beam Pumping Unit.

Beam pumping units are widely used in the oil production industry, but the energy efficiency of this artificial lift machinery is generally low, especially for the low-production well and high-production well in the later stage. There are a number of ways for energy savings in pumping units, with the periodic adjustment of stroke speed and rectification of balance deviation being two important methods. In the paper, an energy saving system for a beam pumping unit (ESS-BPU) based on the Internet of Things (IoT) was proposed.

A computational model for predicting fusion peptide of retroviruses.

As a pivotal domain within envelope protein, fusion peptide (FP) plays a crucial role in pathogenicity and therapeutic intervention. Taken into account the limited FP annotations in NCBI database and absence of FP prediction software, it is urgent and desirable to develop a bioinformatics tool to predict new putative FPs (np-FPs) in retroviruses. In this work, a sequence-based FP model was proposed by combining Hidden Markov Method with similarity comparison.

Computational identification of circular RNAs based on conformational and thermodynamic properties in the flanking introns.

Circular RNAs (circRNAs) were found more than 30 years ago, but have been treated as molecular flukes in a long time. Combining deep sequencing studies with bioinformatics technique, thousands of endogenous circRNAs have been found in mammalian cells, and some researchers have proved that several circRNAs act as competing endogenous RNAs (ceRNAs) to regulate gene expression. However, the mechanism by which the precursor mRNA to be transformed into a circular RNA or a linear mRNA is largely unknown.

ADPRtool: A novel predicting model for identification of ASP-ADP-Ribosylation sites of human proteins.

Post-translational modifications (PTMs) occur in the vast majority of proteins, and they are essential for many protein functions. Computational prediction of the residue location of PTMs enhances the functional characterization of proteins. ADP-Ribosylation is an important type of PTM, because it is implicated in apoptosis, DNA repair, regulation of cell proliferation, and protein synthesis.

An ultrasonic sensor system based on a two-dimensional state method for highway vehicle violation detection applications.

With the continuing growth of highway construction and vehicle use expansion all over the world, highway vehicle traffic rule violation (TRV) detection has become more and more important so as to avoid traffic accidents and injuries in intelligent transportation systems (ITS) and vehicular ad hoc networks (VANETs). Since very few works have contributed to solve the TRV detection problem by moving vehicle measurements and surveillance devices, this paper develops a novel parallel ultrasonic sensor system that can be used to identify the TRV behavior of a host vehicle in real-time. Then a two-dimensional state method is proposed, utilizing the spacial state and time sequential states from the data of two parallel ultrasonic sensors to detect and count the highway vehicle violations.

CarSPred: a computational tool for predicting carbonylation sites of human proteins.

Protein carbonylation is one of the most pervasive oxidative stress-induced post-translational modifications (PTMs), which plays a significant role in the etiology and progression of several human diseases. It has been regarded as a biomarker of oxidative stress due to its relatively early formation and stability compared with other oxidative PTMs. Only a subset of proteins is prone to carbonylation and most carbonyl groups are formed from lysine (K), arginine (R), threonine (T) and proline (P) residues.

A practical application combining wireless sensor networks and Internet of Things: Safety Management System for Tower Crane Groups.

The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body.

ISDTool 2.0: a computational model for predicting immunosuppressive domain of retroviruses.

Immunosuppressive domain (ISD) is a conserved region of transmembrane proteins (TM) in envelope gene (env) of retroviruses. in vitro and vivo, a synthetic peptide (CKS-17) that shows homology to ISD inhibits immune function. Evidence has shown that ISD suppresses lymphocyte proliferation and allows escape from immune effectors of the innate and adaptive arms in mouse immune system.

ISDTool: a computational model for predicting immunosuppressive domain of HERVs.

Human endogenous retroviruses (HERVs) have been found to act as etiological cofactors in several chronic diseases, including cancer, autoimmunity and neurological dysfunction. Immunosuppressive domain (ISD) is a conserved region of transmembrane protein (TM) in envelope gene (env) of retroviruses. In vitro and vivo, evidence has shown that retroviral TM is highly immunosuppressive and a synthetic peptide (CKS-17) that shows homology to ISD inhibits immune function.