Proceedings of the 9th International Conference on Bioinformatics Research and Applications最新文献

{"title":"Exergy and exergy cost analysis of biochemical networks in living systems far from equilibrium","authors":"Assal Selma, F. Malfatti, M. Giani, M. Reini","doi":"10.1145/3569192.3569199","DOIUrl":"https://doi.org/10.1145/3569192.3569199","url":null,"abstract":"Whilst humanity has reached a high level of technological development, finding efficient substitutes to petroleum energy is a challenging task. In this context, metabolically engineered microorganisms are used in biomass production. Considering the availability of data in genomic and metabolic fronts, Escherichia.Coli is one of the primary options for biofuel production, which could be later exploited as a ‘solo’ energy source, or coupled with nowadays available fuels. To survive, an organism must provide an amount of exergy greater than the exergy required to process equilibrium operations. Therefore, extra exergy amounts are needed for a living system to accomplish production, growth and evolution in time, as the above mentioned process is highly irreversible. This paper reviews the available studies on exergy analysis and exergy-cost theory-ECT application, along with the use of flux balance analysis-FBA and flux variability analysis-FVA, as a tool for gaining biological insights. The paper is structured as the following; first, a brief description of exergy analysis and the exergy-cost theory is presented. Second, the exergy analysis application on living cells is discussed through introducing exergy analysis of metabolic networks. Thirdly, the application on E.Coli is explained, highlighting its potential role in biofuel production. Finally, an approach, applied within a current PhD research project regarding the application of the exergy analysis to a generic metabolic network is introduced. In this approach, the exergy costs associated with all the flows present in the targeted network are calculated, according to the ECT. The perspective is to use the exergy cost information for defining additional constraints in the FBA of the metabolic network. Which could provide better insight about organisms and identify directions for the optimization of biomass production, and the enhancement of biofuel use.","PeriodicalId":249004,"journal":{"name":"Proceedings of the 9th International Conference on Bioinformatics Research and Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115935610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Success stories of triterpenoid-based hybrid molecules as new promising anticancer agents: Triterpenoid-driven analogs","authors":"I. Arslan","doi":"10.1145/3569192.3569217","DOIUrl":"https://doi.org/10.1145/3569192.3569217","url":null,"abstract":"Natural product-based hybrid molecules have recently revolutionized promising anticancer results. Triterpenoids represent a wide-spread class of secondary metabolites with a carbon skeleton which contains six isoprene units by the cyclization of squalene. Molecular optimization is frequently necessary for improvement on target specificity, lower toxicity, potency, and stability as well. Lately, to improve the molecular potency some synthetic toolboxes which can access the molecular diversity have been developed. This review showcases structural modification of triterpenoids and their anti-cancer efficacy compared to original compounds.","PeriodicalId":249004,"journal":{"name":"Proceedings of the 9th International Conference on Bioinformatics Research and Applications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116633643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In Silico Drug Repurposing using Knowledge Graph Embeddings for Alzheimer's Disease","authors":"Geesa Daluwatumulle, Rupika Wijesinghe, R. Weerasinghe","doi":"10.1145/3569192.3569203","DOIUrl":"https://doi.org/10.1145/3569192.3569203","url":null,"abstract":"Drug repurposing (DR), also known as drug repositioning, is a method that identifies novel therapeutic uses from existing drugs. This strategy is highly effective, saves time, cost, and has a minimum risk factor when compared with the traditional in vitro and in vivo drug development methodologies. DR is used for difficult to treat, neglected, or incredibly rare diseases. Alzheimer's disease (AD) is categorized as a difficult to treat disease since, no medication is available that can slow down the disease progression without causing severe risk factors. In this context, novel methodologies are vital to find DR candidates for AD. Natural Language Processing (NLP) is garnering popularity due its ability to discover unseen knowledge and complex associations and this study too utilized a NLP approach. The proposed methodology included four main steps. First, the text data that is needed for the study were retrieved, then the information within the unstructured text data were extracted, next, the DR candidates were predicted using a novel hybrid method which included cosine similarity (CS) and link prediction (LP). Finally, the predicted drug candidates were fed into a trained machine learning (ML) model with a specificity of 0.894% and a f1 score of 0.819% and further validated. The analysis showed that some of the candidates which were not approved nor had ongoing clinical trials have enormous potential in treating AD.","PeriodicalId":249004,"journal":{"name":"Proceedings of the 9th International Conference on Bioinformatics Research and Applications","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126990583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Deep Learning Approach to Estimate SpO2 from PPG Signals","authors":"B. Koteska, Ana Madevska Bodanova, Hristina Mitrova, Marija Sidorenko, F. Lehocki","doi":"10.1145/3569192.3569215","DOIUrl":"https://doi.org/10.1145/3569192.3569215","url":null,"abstract":"Blood oxygen saturation level (SpO2) is one of the vital parameters determining the hemostability of a patient, besides heart rate (HR), respiratory rate (RR) and blood preasure (BP). In emergency situations with a high number of injured persons, during the second triage until arrival to a medical facility, continuously following the SpO2 level in real time is of outmost importance. Using a smart patch-like device attached to a injured’s chest that contains a Photoplethysmogram (PPG) sensor, one can obtain the SpO2 parameter. Our interest in the process of the smart patch prototype development is to investigate the monitoring of a blood oxygen saturation level by using the embedded PPG sensor. We explore acquiring the SpO2 by extracting the set of features from the PPG signal utilizing Python toolkit HeartPy in order to model a Deep neural network regressor. The PPG signal is preprocessed by various filtering techniques to remove low/high frequency noise. The model was trained and tested using the clinical data collected from 52 subjects with SpO2 levels varying from 83 - 100%. The best experimental results considering the SpO2 interval [83,95) were achieved with a PPG signal of 10 seconds length (MAPE 2.00% and 7.21% of big errors defined as absolute percentage errors (APE) equal or greater than 5).","PeriodicalId":249004,"journal":{"name":"Proceedings of the 9th International Conference on Bioinformatics Research and Applications","volume":"269 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122921885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Augmented Synthetic Dataset with Structured Light to Develop Ai-Based Methods for Breast Depth Estimation","authors":"Bruno Duarte, Bruno Oliveira, Helena R. Torres, P. Morais, J. Fonseca, J. Vilaça","doi":"10.1145/3569192.3569206","DOIUrl":"https://doi.org/10.1145/3569192.3569206","url":null,"abstract":"Breast interventions are common healthcare procedures that normally require experienced professionals, expensive setups, and high execution times. With the evolution of robot-assisted technologies and image analysis algorithms, new methodologies can be implemented to facilitate the interventions in this area. To enable the introduction of robot-assisted approaches for breast procedures, strategies with real-time capacity and high precision for 3D breast shape estimation are required. In this paper, it is proposed to fuse the structured light (SL) and deep learning (DL) techniques to perform the depth estimation of the breast shape with high precision. First, multiple synthetic datasets of breasts with different printed patterns, resembling the SL technique, are created. Thus, it is possible to take advantage of the pattern's deformation induced by the breast surface in order to improve the quality of the depth information and to study the most suitable design. Then, distinct DL architectures, taken from the literature, were implemented to estimate the breast shape from the created datasets and study the DL architectures’ influence on depth estimation. The results obtained with the introduction of a yellow grid pattern, composed of thin stripes, fused with the DenseNet-161 architecture achieved the best results. Overall, the current study demonstrated the potential of the proposed practice for breast depth estimation or other human body parts in the future when we rely exclusively on 2D images.","PeriodicalId":249004,"journal":{"name":"Proceedings of the 9th International Conference on Bioinformatics Research and Applications","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125885287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A neuro-genetic approach for inferring gene regulatory networks from gene expression data","authors":"Guo Mao, Zhengbin Pang, Jie Liu, K. Zuo","doi":"10.1145/3569192.3569193","DOIUrl":"https://doi.org/10.1145/3569192.3569193","url":null,"abstract":"Accurate prediction of gene regulation rules is important for understanding complex life processes. Existing computational algorithms designed for bulk transcriptome datasets typically require a large number of time points to infer gene regulatory networks (GRNs), are suitable for a small number of genes, and cannot efficiently detect potential regulatory relationships. We propose an approach based on a deep learning framework to reconstruct GRNs from bulk transcriptome datasets, assuming that the expression levels of transcription factors involved in gene regulation are strong predictors of the expression of their target genes. The algorithm uses multilayer perceptrons to infer the regulatory relationship between multiple transcription factors and a gene, and uses genetic algorithms to search for the best regulatory gene combination. The results show that our approach is more accurate than other methods for reconstructing gene regulatory networks on real-world and simulated bulk transcriptome gene expression datasets.","PeriodicalId":249004,"journal":{"name":"Proceedings of the 9th International Conference on Bioinformatics Research and Applications","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124649159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In silico Investigation of Immulina Glycosidic Residues as Immunostimulants by Targeting Penaeus monodon Shrimp Toll-Receptor 9","authors":"T. J. Roxas, Ryan Christian Mailem, A. Kikuchi, L. Tayo","doi":"10.1145/3569192.3569202","DOIUrl":"https://doi.org/10.1145/3569192.3569202","url":null,"abstract":"White Feces Syndrome (WFS) is a disease that causes serious problems in the shrimp aquaculture industry and is highly linked to two bacterial species, namely, Enterocytozoon hepatopenaei (EHP) and Gram-negative Vibrio species. Due to the emergence of new diseases in shrimps and their unclear etiology, such as WFS, there is a need for the development of new therapeutic strategies that can improve the immunity of shrimps. Thus, in this study, we determined glycosidic compounds which can serve as immunostimulants that have high affinity towards P. monodon shrimp TLR9 to induce the NF-κB signaling pathway and strengthen shrimp immunity against viral and bacterial diseases. The glycosidic compounds were obtained from the Immulina polysaccharide. The protein structure was acquired through homology modeling using mouse TLR3 (SMTL ID: 7c77.1) as a template using the SWISS-MODEL webserver. Based on the docking studies, N-acetyl-glucosamine (ca. -6.99 kcal/mol), 2,3-methylfucose (ca. -6.78 kcal/mol), and 2-methyl glycose (ca. -6.66 kcal/mol) were the top-scoring compounds which have high binding affinity towards the target protein. By visualizing the ligand-protein interactions, we learned that ASN512 was the common binding residue among most of the top-scoring compounds and plays a crucial role in ligand-protein binding. Based on the MD studies, all compounds showed low RMSD values, except N-acetyl-glucosamine, indicating good ligand binding to the target protein. In the MMPBSA studies, we found that 2,3-methylfucose had the lowest average binding energy (ca. -41.507 ± 88.52); hence, this glycosidic compound shows the highest affinity towards shrimp TLR9. To conclude, all three top-scoring compounds have highly favorable agonistic binding towards P. monodon TLR9 given their low average binding energy values. To further affirm our conclusions, we recommend the use of in vivo and in vitro tests, as well as longer MD studies for more accurate simulations.","PeriodicalId":249004,"journal":{"name":"Proceedings of the 9th International Conference on Bioinformatics Research and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121586393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CNN classification of variance-based selected topo-maps of EEG","authors":"Tereza Simralova, J. Strobl, V. Piorecká, F. Černý, M. Piorecký","doi":"10.1145/3569192.3569211","DOIUrl":"https://doi.org/10.1145/3569192.3569211","url":null,"abstract":"Epileptic activity in the EEG record can manifest in different ways over time series. A classifier that would alert physicians to the possibility of different types of epileptic activity would be an effective tool. We created image data from EEG records, which we subsequently classified using the SqueezeNet network, which has a promising potential in the field of image classification based on the results so far. On patients whose data the network did not come into contact with during training and validation, we subsequently assessed the accuracy of the classification. The accuracy for each condition was around 80%.","PeriodicalId":249004,"journal":{"name":"Proceedings of the 9th International Conference on Bioinformatics Research and Applications","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132468871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison and validation of pressure and acceleration time-domain waveform models of a smart insole for accurate step count in healthy people","authors":"Armelle M. Ngueleu, C. Batcho, M. Otis","doi":"10.1145/3569192.3569213","DOIUrl":"https://doi.org/10.1145/3569192.3569213","url":null,"abstract":"Several studies have shown good accuracies for step count based on pressure signals of smart insoles in people walking at different speeds. Although smart insoles are often equipped with pressure sensors and accelerometer, no study has focused on comparing the accuracy of step count separately based on pressure and acceleration signals in healthy people. The objectives of this study were to design a waveform model of accelerometer and pressure sensors, and then compare with commercially well-known step count devices and validate these models using manual step counter for step count. Eight healthy participants (age: 39.8±17.56 years old) wore a pair of smart insoles, a GaitUp, and a StepWatchTM and performed the six-minute walking test at walking speeds from 1.62 to 2.22 m/s. Four pressure and one acceleration waveform models were designed and used for the detection of 341 to 412 steps. Accuracies ranged from 99.80%±0.60% to 99.97%±1.38% for right side, and from 99.67%±0.63% to 99.90%±0.05% for left side with pressure waveform models. In addition, the acceleration waveform model provided accuracies of 99.87%±2.49% and 99.84%±4.77% for right and left sides respectively. Step count accuracies using the GaitUp were 99.51%±2.06% for right side, and 99.51%±4.32% for left side. Finally, the StepWatchTM yielded step count accuracies of 99.31%±15.95% and 98.52%±28.06% for right and left sides respectively. These results suggested the smart insole with pressure and acceleration waveform models as more accurate than the StepWatchTM and the GaitUp for step count.","PeriodicalId":249004,"journal":{"name":"Proceedings of the 9th International Conference on Bioinformatics Research and Applications","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131706871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phylogenetic Analysis of the Histone-like Protein (pA104R) Reveals High Conservation among African Swine Fever Virus (ASFV) Variants","authors":"T. J. Roxas, M. C. Gomez, L. Tayo","doi":"10.1145/3569192.3569194","DOIUrl":"https://doi.org/10.1145/3569192.3569194","url":null,"abstract":"The African Swine Fever Virus (ASFV) is a highly lethal virus that causes the death of pigs a week after its symptoms begin to manifest; hence, a mortality rate reaching up to 100%. Because of the crucial role of pork as a food preference worldwide, significant economic losses due to ASF outbreaks have been experienced. Despite the severity of this disease, there is still no known treatment that can successfully cure ASF. Recently, the role of the histone-like protein pA104R in the viral replication of ASFV has been unraveled and is gathering the attention of many researchers as a potential target to inhibit ASFV infectivity. However, little is known about the relationship of this protein with its homologs across variants of ASF. Therefore, in this study, we characterized their relationship and highlight conserved and variable regions that allow for the design of effective inhibitors. We acquired the nucleotide sequences of all pA104R homologs through the tBLASTn program. These sequences were subjected to multiple sequence alignment (MSA), and the evolutionary behavior of the sequences was then mapped out. The resulting tree was produced from 91 sequences taken from the NCBI database and contained five distinct clades. The phylogenetic analysis revealed that variants from clades “C” and “E” were highly variable, reflecting higher frequencies of gene mutation compared to the other clades. The alignment and midpoint-rooted phylogenetic tree showed the high conservation of pA104R across variants of ASFV. The variable residues were also determined. From these results, we conclude that drugs and drug-like compounds that can block the protein-DNA binding sites can be administered to afflicted pigs all over the world due to the high conservation of the protein across virulent strains. Thus, pA104R has high potential as a target protein for the inhibition of ASFV replication and spread.","PeriodicalId":249004,"journal":{"name":"Proceedings of the 9th International Conference on Bioinformatics Research and Applications","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133770603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}