Avian influenza subtype A/H9N2—which infects chickens, reducing egg production by up to 80%—may be transmissible to humans. In humans, this virus is very harmful since it attacks the respiratory system and reproductive tract, replicating in both. Previous attempts to find antiviral candidates capable of inhibiting influenza A/H9N2 transmission were unsuccessful. This study aims to better characterize A/H9N2 to facilitate the discovery of antiviral compounds capable of inhibiting its transmission. The Symmetry of this study is to apply several machine learning methods to perform virtual screening to identify H9N2 antivirus candidates. The parameters used to measure the machine learning model’s quality included accuracy, sensitivity, specificity, balanced accuracy, and receiver operating characteristic score. We found that the extreme gradient boosting method yielded better results in classifying compounds predicted to be suitable antiviral compounds than six other machine learning methods, including logistic regression, k-nearest neighbor analysis, support vector machine, multilayer perceptron, random forest, and gradient boosting. Using this algorithm, we identified 10 candidate synthetic compounds with the highest scores. These high scores predicted that the molecular fingerprint may involve strong bonding characteristics. Thus, we were able to find significant candidates for synthetic H9N2 antivirus compounds and identify the best machine learning method to perform virtual screenings.

There are several phylogenetic tree construction methods that can be used to illustrate the spread of disease epidemics. One of the methods used is probability-based maximum likelihood. This paper explains how to identify the spread of the SARS epidemic in the world using the formation of phylogenetic trees using the maximum likelihood method. The output obtained was a description of the spread of SARS virus with the selection of tree candidates after performing a heuristic search of the Stepwise Addition method. The result of the research showed that the closest distance to the palm civet is GZ 02/18/03 indicating that the initial spread of the SARS epidemic started from Guangzhou.

Background:Multiple sequence alignment is a method of getting genomic relationships between 3 sequences or more. In multiple alignments, there are 3 mutation network analyses, namely topological network system, mutation region network and network system of mutation mode. In general, the three analyses show stable and unstable regions that map mutation regions. This area of ​​mutation is described further in a phylogenetic tree which simultaneously illustrates the path of the spread of an epidemic, the Severe Acute Respiratory Syndrome (SARS) epidemic. The process of spreading the SARS viruses, in this case, is described as the process of phylogenetic tree formation, and as a novelty of this research, multiple alignments in the process are analyzed in detail and then optimized with genetic algorithms.Methods:The data used to form the phylogenetic tree for the spread of the SARS epidemic are 14 DNA sequences which are then optimized by using genetic algorithms. The phylogenetic tree is constructed by using the neighbor-joining algorithm with a distance matrix that the intended distance is the genetic distance obtained from sequence alignment by using the Needleman Wunsch Algorithm.Results & Conclusion:The results of the analysis obtained 3649 stable areas and 19 unstable areas. The results of phylogenetic tree from the network system analysis indicated that the spread of the SARS epidemic extended from Guangzhou 16/12/02 to Zhongshan 27/12/02, then spread simultaneously to Guangzhou 18/02/03 and Guangzhou hospital. After that, the virus reached Metropole, Zhongshan, Hongkong, Singapore, Taiwan, Hong kong, and Hanoi which then continued to Guangzhou 01/01/03 and Toronto at once. The results of the mutation region network system demonstrate decomposition of orthogonal mutations in the 1st order arc.

Multiple Alignment (MA) is a particularly important tool for studying the viral genome and determine the evolutionary process of the specific virus. Application of MA in the case of the spread of the Severe acute respiratory syndrome (SARS) epidemic is an interesting thing because this virus epidemic a few years ago spread so quickly that medical attention in many countries. Although there has been a lot of software to process multiple sequences, but the use of pairwise alignment to process MA is very important to consider. In previous research, the alignment between the sequences to process MA algorithm, Super Pairwise Alignment, but in this study used a dynamic programming algorithm Needleman wunchs simulated in Matlab. From the analysis of MA obtained and stable region and unstable which indicates the position where the mutation occurs, the system network topology that produced the phylogenetic tree of the SARS epidemic distance method, and system area networks mutation.

MERS-CoV or generally called as Middle East Respiratory Syndrome Coronavirus, a respiratory disease syndrome caused by a corona virus that attacks the respiratory tract ranging from mild to severe acute indication of fever, cough and shortness of breath. The cases happened relate to the countries in the Arabian Peninsula (Middle East) and there were 356 deaths have been reported due to the spread of the epidemic MERS. The data used in the case of MERS are the data DNA sequences taken from Genbank, the online database of the United States that stores the results of molecular biological experiments from all over the world (http://www.ncbi.nlm.nih.gov). In this case, bioinformatics plays an important role of reading sequences of DNA and genetic information by using the main device in the form of software that is supported by the availability of the Internet, while the analysis there in made and proven with mathematical methods. In similar research conducted by molecular biologists and physicians, the process of DNA sequencing is done with software that is already available like BLAST. In order to determine the MERS geographical distribution patterns in the Arabian Peninsula is done with program Clustal W, Bayesian, Phylip, etc. In this study, the writer use the Matlab simulation for all processes starting sequence alignment, counting the number of transitions and transversion substitutions for each sequence and its location up to the process of forming a phylogenetic tree that figures out the pattern of spread of the epidemic MERS. Mathematical analysis performed on a decline in the formula is to find Kimura evolutionary models and the process of forming a phylogenetic tree (the pattern of the epidemic MERS distribution) with neighbor joining algorithm. Finally it was obtained the pattern of geographical spread with 6 groups epidemic of MERS which ultimately turns out that all the MERS viruses that were spread in the Arabian Peninsula everything are almost the same as the virus sequence found in al-Hasa.

Zika virus that became a hot issue in the media recent years behind is very interesting to study, especially the Zika virus has similar to infection to Dengue fever. The virus that is infect to humans through mosquito bites by Aedes genus, Especially Aedes aegypti is identical mosquito that spread Dengue, yellow fever and chikungunya. In Brazil, an increase syndrome Zika virus infection in the community have observed by local health authorities, and also in northeast Brazil an increase of microcephaly condition in babies born. In addition, the Zika virus sporadic infection has reported by approximately 13 Americas countries that show very rapid expansion, and also Indonesia, the euphoria discussed increasingly after the positive patient infected by Zika virus has discovered in Jambi on January 2016. Moving on from this, the authors wanted to know how the sequences protein Zika virus when compared with the Dengue virus, the percentage of identical sequence and also the calculation of local alignment its using the Smith Waterman algorithm. In addition it will also be known genetic mutations that occur in Zika virus from its origin until Zika virus into Indonesia and phylogenetic tree spread of the virus to get to Jambi. So the researcher construct sequence alignment tools by using graphical user interface in MATLAB program based on Smith Waterman algorithm, and also a link in the system with the browser as an option for online data retrieval. From the result of sequence alignment by MATLAB and BLAST, that the identical values of sequence using MATLAB is higher than BLAST values. Likewise, the duration of computation that MATLAB computation is more effective than BLAST computation.