24 research outputs found
A New Methodology to Exploit Predictive Power in (Open, High, Low, Close) Data
Prediction of financial markets using neural networks and other techniques has predominately focused on the close price. Here, in contrast, the concept of a mid-price based on an Open, High, Low, Close (OHLC) data structure is proposed as a prediction target and shown to be a significantly easier target to forecast, suggesting previous works have attempted to extract predictive power from OHLC data in the wrong context. A prediction framework incorporating a factor discovery and mining process is developed using Randomised Decision Trees, with Long Short Term Memory Recurrent Neural Networks subsequently demonstrating remarkable predictive capabilities of up to 50.73% better than random (75.42% accuracy) on hourly data based on the FGBL German Bund futures contract, and 42.5% better than random (72.04% accuracy) on a comparison Bitcoin dataset
Deep Candlestick Mining
A data mining process we name Deep Candlestick Mining (DCM) is developed using Randomised Decision Trees, Long Short Term Memory Recurrent Neural Networks and k-means++, and is shown to discover candlestick patterns significantly outperforming traditional ones. A test for the predictive ability of novel versus traditional candlestick patterns is devised using all significant candlestick patterns within the traditional or deep mined categories. The deep mined candlestick system demonstrates a remarkable ability to outperform the traditional system by 75.2% and 92.6% on the German Bund 10-year futures contract and EURUSD hourly data
Mapping HIV-1 Vaccine Induced T-Cell Responses: Bias towards Less-Conserved Regions and Potential Impact on Vaccine Efficacy in the Step Study
T cell directed HIV vaccines are based upon the induction of CD8+ T cell memory responses that would be effective in inhibiting infection and subsequent replication of an infecting HIV-1 strain, a process that requires a match or near-match between the epitope induced by vaccination and the infecting viral strain. We compared the frequency and specificity of the CTL epitope responses elicited by the replication-defective Ad5 gag/pol/nef vaccine used in the Step trial with the likelihood of encountering those epitopes among recently sequenced Clade B isolates of HIV-1. Among vaccinees with detectable 15-mer peptide pool ELISpot responses, there was a median of four (one Gag, one Nef and two Pol) CD8 epitopes per vaccinee detected by 9-mer peptide ELISpot assay. Importantly, frequency analysis of the mapped epitopes indicated that there was a significant skewing of the T cell response; variable epitopes were detected more frequently than would be expected from an unbiased sampling of the vaccine sequences. Correspondingly, the most highly conserved epitopes in Gag, Pol, and Nef (defined by presence in >80% of sequences currently in the Los Alamos database www.hiv.lanl.gov) were detected at a lower frequency than unbiased sampling, similar to the frequency reported for responses to natural infection, suggesting potential epitope masking of these responses. This may be a generic mechanism used by the virus in both contexts to escape effective T cell immune surveillance. The disappointing results of the Step trial raise the bar for future HIV vaccine candidates. This report highlights the bias towards less-conserved epitopes present in the same vaccine used in the Step trial. Development of vaccine strategies that can elicit a greater breadth of responses, and towards conserved regions of the genome in particular, are critical requirements for effective T-cell based vaccines against HIV-1
Human coronavirus OC43 3CL protease and the potential of ML188 as a broad-spectrum lead compound: Homology modelling and molecular dynamic studies
BACKGROUND: The coronavirus 3 chymotrypsin-like protease (3CL(pro)) is a validated target in the design of potential anticoronavirus inhibitors. The high degree of homology within the protease’s active site and substrate conservation supports the identification of broad spectrum lead compounds. A previous study identified the compound ML188, also termed 16R, as an inhibitor of the Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) 3CL(pro). This study will detail the generation of a homology model of the 3CL(pro) of the human coronavirus OC43 and determine the potential of 16R to form a broad-spectrum lead compound. MODELLER was used to generate a suitable three-dimensional model of the OC43 3CL(pro) and the Prime module of Schrӧdinger predicted the binding conformation and free energy of binding of 16R within the 3CL(pro) active site. Molecular dynamics further confirmed ligand stability and hydrogen bonding networks. RESULTS: A high quality homology model of the OC43 3CL(pro) was successfully generated in an active conformation. Further studies reproduced the binding pose of 16R within the active site of the generated model, where its free energy of binding was shown to equal that of the 3CL(pro) of SARS-CoV, a receptor it is experimentally proven to inhibit. The stability of the ligand was subsequently confirmed by molecular dynamics. CONCLUSION: The lead compound 16R may represent a broad-spectrum inhibitor of the 3CL(pro) of OC43 and potentially other coronaviruses. This study provides an atomistic structure of the 3CL(pro) of OC43 and supports further experimental validation of the inhibitory effects of 16R. These findings further confirm that the 3CL(pro) of coronaviruses can be inhibited by broad spectrum lead compounds
Molecular dynamics simulations of the docking of substituted N5-deazapterins to dihydrofolate reductase
Orientations of the deazapterin ring and the conformational preferences of groups appended to the deazapterin ring in a set of 8-substituted deazapterin cations docked into the dihydrofolate reductase (DHFR) binding site have been investigated using a methodology based on the simulated annealing technique within molecular dynamics (MD) simulations. Of five possible binding pockets for the 8-substituents, identified from a preliminary manual docking study, one has been definitively eliminated after an analysis of MD trajectories, while another remains uncertain. Using a new method based on standard thermodynamic cycles and a linear approximation of polar and non-polar free energy contributions from MD averages, binding affinities of the different ligands in each binding site have been correlated with experimental dissociation constants. The study has provided insights into structure-activity relation-ships for use in the design of modified inhibitors of DHFR
A Theoretical-Study of Aniline and Some Derivatives in Their Ground-States
Geometries and energies of some para-substituted N,N-dimethylaniline derivatives have been calculated using AM1 and ab initio methods for planar and various pyramidal structures with full geometry optimization. The calculated geometry characteristics for aniline show the ability of some theoretical methods to reproduce accurately the experimental data. The influence and interdependence of rotation and inversion angles around C-NX of the amino group are discussed in relation to the nature of the substituents on dimethylaniline. Qualitative and quantitative rules are formulated for the structural properties of these compounds