ORAL PRESENTATION SCHEDULE INTERNATIONAL CONFERENCE ON BIOINFORMATICS (INCOB) 2019 UNIVERSITAS YARSI, JAKARTA, INDONESIA SEPTEMBER 10-12, 2019 DAY/DATE TIME Workshop Room 1 Workshop Room 2 Workshop Room 3 Tue, Sept 10, 1:45-2:45 Theme I: Sequencing and NGS Theme II: Protein structure, Theme III: Immuno informatics and 2019 PM data analysis function and interaction host pathogen interactions 1:45-2:00 O-02: Angana Chakraborty: O-01: Abel Avitesh: Bigram-PGK: O-05: Fransiskus Xaverius Ivan: Rule- PM conLSH: Context based phosphoglycerylation prediction based meta-analysis reveals the major Locality Sensitive Hashing for using the technique of bigram role of PB2 in influencing influenza A Mapping of noisy SMRT Reads probabilities of position specific virus virulence in mice scoring matrix 2:00-2:15 O-06: Garethe Price: Galaxy O-04: Binh Phy Nguyen: O-22: Sataruda Prakash Singh: Design PM Australia - a truly national Classification of Adaptor Proteins of precise vaccine construct against open-source bioinformatics using Recurrent Neural Networks visceral leishmaniasis through platform and PSSM Profiles predicted ensemble epitope: a contemporary approach
2:15-2:30 O-31: Yasubumi Sakakibara: O-07: Hui Liu: MADOKA: An Ultra- O-44: Asif M Khan: Identification of PM An improved de novo genome fast Approach for Large-Scale highly conserved, serotype-specific assembly of the common Protein Structure Similarity dengue virus sequences: implications marmoset genome yields Searching for vaccine design improved contiguity and increased mapping rates of sequence data 2:30-2:45 O-32: Younghi Lee: Differential O-45: Alhadi Bustamam: O-47: Shoba Ranganathan: Prediction PM alternative splicing regulation Performance of Rotation Forest of novel mouseTLR9 agonists using a among hepatocellular Ensemble Classifier and Feature random forest approach carcinoma with different risk Extractor in Predicting Protein factors Interactions Using Amino Acid Sequences 3:00-4:30 Theme IV: Genomics and Theme V: Tools, databases and web Theme VI: Network biology and PM Evolutionary Biology services in Bioinformatics interaction networks 3:00-3:15 O-10: Jing Li: Genome-wide O-23: Sheng-Yao Su: EpiMOLAS: An O-19: Rama Kalia: A module PM identification, phylogeny, and Intuitive Web-based Framework for refinement approach to find expression analysis of the SBP- Genome-wide DNA Methylation functionally significant communities box gene family in Analysis in molecular networks Euphorbiaceae
3:15-3:30 O-48: Reeki Emirzal: O-28: Tsukasa Fukunaga: Logicome O-20: Rama Kalia: A module PM Phylogenetic analysis of Type Profiler: Exhaustive detection of refinement approach to find IX Secretion System (T9SS) statistically significant logic functionally significant communities protein components revealed relationships from comparative in molecular networks that PorR undergoes omics data horizontal gene transfer 3:30-3:45 O-41: Yen-Hua Huang: O-39: Xuan Zhang: JCDB: a O-30: Xioshi Zhong: GO2Vec: PM Deconvolution of bulk gene comprehensive knowledge Transforming GO Terms and Proteins expression profiles from database for Jatropha curcas, an to Vector Representations Using complex tissues to quantify emerging model for woody energy Graph Embeddings subsets of immune cells plants 3:45-4:00 O-18: Rajith Vidanaarachchi: O-46: Zhen Yang: CMTTdb: The O-33: Young-Rae Cho: LePrimAlign: PM IMPARO: Inferring Microbial Cancer Molecular Targeted Therapy local entropy-based alignment of PPI Interactions through Database networks to predict conserved Parameter Optimisation modules 4:00-4:15 O35: Yung-Keun Kwon: Effects O-13: Kitty Lo: scDC: Single cell PM of ordered mutations on differential composition analysis dynamics in signaling networks
4:15-4:30 O-49: Jing Li: Genome-wide O-16: Pengyi Yang: scReClassify: PM identification, phylogeny, and post hoc cell type classification of expression analysis of the SBP- single-cell RNA-seq data box gene family in Euphorbiaceae Wed, Sept 11:45-12:45 Theme VII: Mass spectrometry Theme VIII: Genome wide Theme IX: Machine learning, AI and 11, 2019 PM and nano-bioinformatics association studies (GWAS) and novel algorithms-I Biomarker discovery 11:45-12.00 O-03: Anupam Nath Jha: O-14: Kyungsook Han: Finding O-11: Jinyan Li: Instance-Based PM Computational analysis of prognostic gene pairs for cancer Learning for Personalized Cancer Silver nanoparticle - human from patient-specific gene networks Diagnosis and Treatment Planning serum albumin complex 12:00-12.15 O-08: Jang-Jih Lu: Statistical O-25: Srinivasulu YS: O-12: Jinyan LI: DDI-PULearn: a novel PM Considerations and Machine Characterization of risk genes of positive-unlabeled learning method Learning Approaches for Rapid autism spectrum disorders using for large-scale prediction of drug-drug Strain Typing of gene expression profiles interactions Staphylococcus haemolyticus based on Matrix-Assisted Laser Desorption Ionization- Time-of Flight Mass Spectrometry
12:15-12:30 O-09: Jia-Ming Chang: O-34: Yun Zheng: The O-15: Le Ou-Yang: Predicting PM MS2CNN: Predicting MS/MS transcriptome variations of Panax Synthetic Lethal Interactions in spectrum based on protein notoginseng roots treated with Human Cancers using Graph sequence by Deep different forms of nitrogen Regularized Self-Representative Convolutional Neural fertilizers Matrix Factorization Networks 12:30-12:45 O-42: Tzong-Yi Lee: Rapid O-36: Zhixun Zhao: Identification of O-17: Pengyi Yang: Autoencoder- PM Classification of Group B Lung Cancer Gene Markers through based cluster ensembles for single-cell Streptococcus Serotypes kernel Maximum Mean Discrepancy RNA-seq data analysis based on Matrix-Assisted and Information Entropy Laser Desorption Ionization- Time of Flight Mass Spectrometry and Machine Learning Techniques Thu, Sept 12, 11:00-12:00 Theme X: Machine learning, AI NA NA 2019 PM and novel algorithms-II 11:00-11:15 O-27: Susanto Rahardja: AM Enhancer Identification and Classification using One-Hot Encoding and Ensemble Convolutional Neural Networks
11:15-11:30 O-38: Dimitri Perrin: AM Improving CRISPR guide design with consensus approaches 11:30-11:45 O-40: Ling Zou: Predicting AM synergistic drugs using gradient tree boosting based on features extracted from drug-protein heterogeneous network 11:45-12:00 O-43: Kuo-Ching Liang: PM MetaVelvet-DL: a MetaVelvet deep learning extension for de novo metagenomics assembly 1:00-1:45 Theme XI: Machine learning, Theme XII: Disease data modeling NA PM AI and novel algorithms-III and integrative Biology
1:00-1:15 O-21: Lun Li: A novel O-24: Shobana Sundar: Rv0807, a PM constrained reconstruction putative phospholipase A2 of model towards high- Mycobacterium tuberculosis; resolution sub-tomogram Elucidation through sequence averaging analysis, homology modeling, molecular docking and molecular dynamics studies of potential substrates and inhibitors 1:15-1:30 O-37: Dhillon Sarinder Kaur: O-26: Sudipto Saha: Computational PM An Automated 3D Modelling approach to target USP28 for Pipeline for Constructing 3D regulating Myc Models of Monogenean Hardpart Using Machine Learning Techniques 1:30-1:45 O-50: Susanto Rahardja: O-29: Vivitri Dewi Prasastry: PM iEnhancer-ECNN: Identifying Structure-based Discovery of Novel enhancer and their strength Inhibitors of Mycobacterium using Ensemble of tuberculosis CYP121 from Convolutional Neural Indonesian Natural Products Networks
1:45-2:00 O-51: Asif M. Khan: A systematic PM bioinformatics approach for large- scale identification and characterization of host-pathogen shared sequences
Recommend
More recommend
