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Pharmaceutical industries are interested in Cysteine-stabilized peptides because they offer an array bioactive properties while being highly stable under a range of physiological conditions. However, it is widely appreciated that only a small fraction of this type of peptides have been experimentally discovered while a large number remain unidentified. However, identification of these cysteine-stabilized...
Lack of safety and efficacy are the two major reasons for the failures of drug candidates in drug discovery and development. Reliable prediction of blood-brain barrier permeation even before chemical synthesis still remains as one of the major challenges in drug discovery. New approaches and models that are reliable and can reduce experimental evaluations of pre-clinical candidates are in urgent need...
Modern drug discovery organizations generate large volumes of SAR data. A promising methodology that can be used to mine this chemical data to identify novel structure-activity relationships is the matched molecular pair (MMP) methodology. However, before the full potential of the MMP methodology can be utilized, a MMP identification method that is capable of identifying all MMPs in large chemical...
In this study, we compared three types of word assignment to investigate topic coherence and task performance in Latent Dirichlet Allocation (LDA). We randomly selected 18,000 news articles consists of the categories of finance, life, and politics with 176,224 unigram, 863,680 compound, and 938,206 mixture in total. The result shows that our unigram-based model has high interpretability and topic...
The figures found in biomedical literature are a vital part of biomedical research, education and clinical decision. The multitude of their modalities and the lack of corresponding meta-data, constitute search and information retrieval a difficult task. We present multi-label modality classification approaches for biomedical figures. In particular, we investigate using both simple and compound figures...
In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further...
Complex networks exist widely in nature and human society, from the Internet to chemical reactions, biological food chain, and then to human society, interpersonal relationships, cooperation between people, science and technology citation and so show a complex network topology characteristics. Network pharmacology is based on the theory of system biology, network analysis of biological systems, select...
In machine learning, interpretability refers to understand the underlying behavior of the prediction of a model in order to identify diagnosis criteria and/or new rules from its output. Interpretability contributes to increase the usability of the method. Also, it is relevant in decision support systems, such as in medical applications. White-box models like tree-based, rule-based and linear models...
Aroma analysis follows a well-established procedure which provides a list of odorants that contribute to a given food aroma. However, such a procedure does not allow establishing the actual sensory profile of the food because the perceptual influence of mixed odorants is poorly considered. To improve the aroma analysis efficiency, we explored an innovative strategy which combines classical aroma analysis...
Formation energy is one of the most important properties of a compound that is directly related to its stability. More negative the formation energy, the more stable the compound is likely to be. Here we describe the development and deployment of predictive models for formation energy, given the chemical composition of the material. The data-driven models described here are built using nearly 100,000...
The need for efficiency and effectiveness lead to increasing the involvement of robots in the drug development process. A predictive modeling concept proposed in this paper refers to optimizing the robot movements in a laboratory environment during the experimentation. Trajectory planning is data-driven approach that relies on the interaction of the drug compound and the target. Optimal solution for...
Remaining useful life (RUL) has been attached great importance for the health management of stochastic degrading systems. However, current studies place main focus on continuous degradation processes of systems without the consideration of randomly arriving shocks from changes in inner conditions or external environments. In this paper, we present a new prognostic model to characterize the continuous...
Thermal cycling reliability test and finite element analysis have been conducted for plastic ball grid array assembly with Sn63Pb37 solder. Based on the thermal cycling test results, a two-parameter Weibull distribution model was used to determine the characteristic time to failure of plastic ball grid array assembly. Besides, cross-sectioning and optical microscope examination were utilized to identify...
Electrical discharge plasma is an effective and versatile advanced oxidation process due to the formation of reactive species such as hydroxyl radicals and hydroperoxyl radicals. The technology requires no chemical additions, can degrade a broad range of contaminants, and produces no residual waste. Plasma treatment also includes a broad range of other treatment mechanisms, including electron-based...
Oral cancer is a type of cancer which targets mouth and surrounding tissues. It includes, lips, cheeks, tongue, sinuses, throat. Oral cancer could be life threatening, if not diagnosed in early stages. American Cancer Society says that men are at more risk than women. Oral cancer can be treated like any other cancers. But still the efficacy of the drugs is questionable. Hence, an attempt was tried...
An experimental investigation has been carried out to characterize and discriminate seven saffron samples and to verify their declared geographical origin using a voltammetric electronic tongue (VE-tongue). The ability of multivariable analysis methods such as Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) to classify the saffron samples according to their geographical origin...
Batch adsorption equilibrium of the sulfur compounds from diesel oil using two types of commercial activated carbon was studied in a two-level factorial experimental design method. This technique has been used to investigate the impacts of several factors controlling the adsorption process, such as source of sorbent material, amount of sorbent material used, and temperature. High percentages of adsorption...
In the context of drug discovery, a key problem is the identification of candidate molecules that affect proteins associated with diseases. Inside Janssen Pharmaceutical, the Chemo genomics project aims to derive new candidates from existing experiments through a set of machine learning predictor programs, written in single-node C++. These programs take a long time to run and are inherently parallel,...
This paper presents a hybrid model for electricity price forecasting with focus on price spikes predictions. Nowadays, short-term forecasts have become increasingly important since the rise of the competitive spot electricity markets. A two-layered model is introduced for forecasting 7-days ahead hourly electricity price values of electricity spot market. Due to the importance of improved analysis...
Fusarium circinatum is a disease-causing fungal agent responsible for pitch canker disease in pine trees. In this study, the cytochrome b protein which plays an important role in electron transport chain for respiration is taken as a crucial target for developing anti-fungal inhibitors. We predicted the protein model of cytochrome b in Fusarium circinatum based on the Saccharomyces cytochrome b template...
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