① 연구실명 : Computational Biology and Bioinformatics Lab
② 지도교수명 : 발라찬드란마나발란 교수 ( Prof. Balachandran Manavalan)
③ 연구실 소개 (https://balalab-skku.org/)
In the CBBL, we mainly focus on investigating, developing, and deploying cutting-edge bioinformatics tools using AI-based machine learning techniques to understand and address the challenging problems in genomics and molecular biology. In particular, we are designing computational methods to predict DNA function prediction (Enhancers, replication origin sites, and hypersensitive sites), DNA/RNA modification sites, RNA subcellular localization, and RNA splicing sites. Also, we are developing methods to identify peptide therapeutic functions, protein-specific functions, and post-translational modification sites based on sequence information. Furthermore, we are expanding our research into the areas of drug discovery and neoantigen prediction.
④ 연구분야
"Bioinformatics / Artificial intelligence / Data Mining / Big data and functional genomics / Peptide drug design / Epigenetic data analysis / Predicting DNA/RNA bindings / roteins and their residues / Sequence-based biomolecular function prediction"
⑤ 대표연구 실적
■ "(2022) Phasit Charoenkwan, Nalini Schaduangrat, Pietro Lio', Mohammad Ali Moni, Watshara Shoombuatong, Balachandran Manavalan. Computational prediction and interpretation of druggable proteins using a stacked ensemble-learning framework. iScience. 25(9):104883
■ (2022) Adeel Malik, Sathiyamoorthy Subramaniyam, Chang-Bae Kim, Balachandran Manavalan. SortPred: The first machine learning based predictor to identify bacterial sortases and their classes using sequence-derived information. Computational and Structural Biotechnology Journal. 20:165-174
■ (2022) Le Thi Phan, Hyun Woo Park, Thejkiran Pitti, Thirumurthy Madhavan, Young-Jun Jeon, Balachandran Manavalan. MLACP 2.0: An updated machine learning tool for anticancer peptide prediction. Computational and Structural Biotechnology Journal. 20:4473-4480.
■ (2022) Phasit Charoenkwan, Wararat Chiangjong, Chanin Nantasenamat, Mohammad Ali Moni, Pietro Lio', Balachandran Manavalan, Watshara Shoombuatong. SCMTHP: A New Approach for Identifying and Characterizing of Tumor-Homing Peptides Using Estimated Propensity Scores of Amino Acids. Pharmaceutics. 14(1):122
■ (2022) Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, Mohammad Ali Moni, Pietro Lio', Balachandran Manavalan, Watshara Shoombuatong. StackDPPIV: A novel computational approach for accurate prediction of dipeptidyl peptidase IV (DPP-IV) inhibitory peptides. Methods. 204:189-198
■ (2022) Md Mehedi Hasan, Sho Tsukiyama, Jae Youl Cho, Hiroyuki Kurata, Md Ashad Alam, Xiaowen Liu, Balachandran Manavalan, Hong-Wen Deng. Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy. Molecular Therapy. 30(8):2856-2867
■ (2022) Phasit Charoenkwan, Nalini Schaduangrat, Pietro Lio', Mohammad Ali Moni, Balachandran Manavalan, Watshara Shoombuatong. NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides. Computers in Biology and Medicine. 148:105700
■ (2022) Young-Jun Jeon, Md Mehedi Hasan, Hyun Woo Park, Ki Wook Lee, Balachandran Manavalan. TACOS: a novel approach for accurate prediction of cell-specific long noncoding RNAs subcellular localization. Briefings in Bioinformatics. 23(4)
■ (2022) Shaherin Basith, Gwang Lee, Balachandran Manavalan. STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction. Briefings in Bioinformatics. 23(1)
■ (2022) Watshara Shoombuatong, Shaherin Basith, Thejkiran Pitti, Gwang Lee, Balachandran Manavalan. THRONE: A New Approach for Accurate Prediction of Human RNA N7-Methylguanosine Sites. Journal of Molecular Biology. 434(11):167549
■ (2022) Balachandran Manavalan, Shaherin Basith, Gwang Lee. Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2. Briefings in Bioinformatics. 23(1)
■ (2022) Hiroyuki Kurata, Sho Tsukiyama, Balachandran Manavalan. iACVP: markedly enhanced identification of anti-coronavirus peptides using a dataset-specific word2vec model. Briefings in Bioinformatics. 23(4)
■ (2022) Phasit Charoenkwan, Nalini Schaduangrat, Mohammad Ali Moni, Pietro Lio', Balachandran Manavalan, Watshara Shoombuatong. SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins. Computers in Biology and Medicine. 146:105704
■ (2022) Shaherin Basith, Hye Jin Chang, Saraswathy Nithiyanandam, Tae Hwan Shin, Balachandran Manavalan, Gwang Lee. Recent Trends on the Development of Machine Learning Approaches for the Prediction of Lysine Acetylation Sites. Current Medicinal Chemistry. 29(2):235-250
■ (2022) Balachandran Manavalan, Mahesh Chandra Patra. MLCPP 2.0: An Updated Cell-penetrating Peptides and Their Uptake Efficiency Predictor. Journal of Molecular Biology. 434(11):167604
■ (2022) Wenjia He, Yi Jiang, Junru Jin, Zhongshen Li, Jiaojiao Zhao, Balachandran Manavalan, Ran Su, Xin Gao, Leyi Wei. Accelerating bioactive peptide discovery via mutual information-based meta-learning. Briefings in Bioinformatics. 23(1)
■ (2021) Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, Balachandran Manavalan, Watshara Shoombuatong. BERT4Bitter: a bidirectional encoder representation from transformers (BERT)-based model for improving the prediction of bitter peptides. Bioinformatics. 26
■ (2021) Md Mehedi Hasan, Shaherin Basith, Mst Shamima Khatun, Gwang Lee, Balachandran Manavalan, Hiroyuki Kurata. Meta-i6mA: an interspecies predictor for identifying DNA N6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework. Briefings in Bioinformatics. 22(3)
■ (2021) Leyi Wei, Wenjia He, Adeel Malik, Ran Su, Lizhen Cui, Balachandran Manavalan. Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework. Briefings in Bioinformatics. 22(4)
■ (2021) Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, Mohammad Ali Moni, Balachandran Manavalan, Watshara Shoombuatong. UMPred-FRL: A New Approach for Accurate Prediction of Umami Peptides Using Feature Representation Learning. International journal of molecular sciences. 22(23):13124
■ (2021) Shaherin Basith, Md Mehedi Hasan, Gwang Lee, Leyi Wei, Balachandran Manavalan. Integrative machine learning framework for the identification of cell-specific enhancers from the human genome. Briefings in Bioinformatics. 22(6)
■ (2021) Phasit Charoenkwan, Wararat Chiangjong, Chanin Nantasenamat, Md Mehedi Hasan, Balachandran Manavalan, Watshara Shoombuatong. StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides. Briefings in Bioinformatics. 22(6)
■ (2021) Md Mehedi Hasan, Md Ashad Alam, Watshara Shoombuatong, Hong-Wen Deng, Balachandran Manavalan, Hiroyuki Kurata. NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning. Briefings in Bioinformatics. 22(6)
■ (2021) Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, Gwang Lee. Computational prediction of species-specific yeast DNA replication origin via iterative feature representation. Briefings in Bioinformatics. 22(4)
■ (2021) Md Mehedi Hasan, Watshara Shoombuatong, Hiroyuki Kurata, Balachandran Manavalan. Critical evaluation of web-based DNA N6-methyladenine site prediction tools. Briefings in Functional Genomics. 20(4):258-272
■ (2020) Md Mehedi Hasan, Nalini Schaduangrat, Shaherin Basith, Gwang Lee, Watshara Shoombuatong, Balachandran Manavalan. HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation. Bioinformatics. 36(11):3350-3356
■ (2020) Ran Su, Jie Hu, Quan Zou, Balachandran Manavalan, Leyi Wei. Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools. Briefings in Bioinformatics. 21(2):408-420
■ (2020) Balachandran Manavalan, Md Mehedi Hasan, Shaherin Basith, Vijayakumar Gosu, Tae-Hwan Shin, Gwang Lee. Empirical Comparison and Analysis of Web-Based DNA N 4-Methylcytosine Site Prediction Tools. Molecular Therapy Nucleic Acids. 22:406-420
■ (2020) Shaherin Basith, Balachandran Manavalan, Tae Hwan Shin, Gwang Lee. Machine intelligence in peptide therapeutics: A next-generation tool for rapid disease screening. Medicinal Research Reviews. 40(4):1276-1314
■ (2020) Rajiv G Govindaraj, Sathiyamoorthy Subramaniyam, Balachandran Manavalan. Extremely-randomized-tree-based Prediction of N 6-Methyladenosine Sites in Saccharomyces cerevisiae. Current Genomic. 21(1):26-33.
■ (2019) Vinothini Boopathi, Sathiyamoorthy Subramaniyam, Adeel Malik, Gwang Lee, Balachandran Manavalan, Deok-Chun Yang. mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides. International Journal of Molecular Sciences. 20(8):1964
■ (2019) Balachandran Manavalan, Kunihiro Kuwajima, Jooyoung Lee. PFDB: A standardized protein folding database with temperature correction. Scientific Reports. 9(1):1588
■ (2019) Leyi Wei, Ran Su, Shasha Luan, Zhijun Liao, Balachandran Manavalan, Quan Zou, Xiaolong Shi. Iterative feature representations improve N4-methylcytosine site prediction. Bioinformatics. 35(23):4930-4937
■ (2019) Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, Da Yeon Lee, Leyi Wei, Gwang Lee. 4mCpred-EL: An Ensemble Learning Framework for Identification of DNA N4-methylcytosine Sites in the Mouse Genome. Cells. 8(11):1332
■ (2019) Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, Leyi Wei, Gwang Lee. AtbPpred: A Robust Sequence-Based Prediction of Anti-Tubercular Peptides Using Extremely Randomized Trees. Computational and Structural Biotechnology Journal. 17:972-981
■ (2019) Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, Leyi Wei, Gwang Lee. mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation. Bioinformatics. 35(16):2757-2765
■ (2019) Shaherin Basith, Balachandran Manavalan, Tae Hwan Shin, Gwang Lee. SDM6A: A Web-Based Integrative Machine-Learning Framework for Predicting 6mA Sites in the Rice Genome. Molecular Therapy Nucleic Acids. 18:131-141
■ (2019) Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, Leyi Wei, Gwang Lee. Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation. Molecular Therapy Nucleic Acids. 16:733-744
■ (2018) Shaherin Basith, Balachandran Manavalan, Tae Hwan Shin, Gwang Lee. iGHBP: Computational identification of growth hormone binding proteins from sequences using extremely randomised tree. Computational and Structural Biotechnology Journal. 16:412-420
■ (2018) Balachandran Manavalan, Sathiyamoorthy Subramaniyam, Tae Hwan Shin, Myeong Ok Kim, Gwang Lee. Machine-Learning-Based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency with Improved Accuracy. Journal of Proteome Research. 17(8):2715-2726
■ (2018) Balachandran Manavalan, Tae H Shin, Gwang Lee. PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine. Frontiers in Microbiology. 9:476.
■ (2018) Balachandran Manavalan, Tae H Shin, Myeong O Kim, Gwang Lee. AIPpred: Sequence-Based Prediction of Anti-inflammatory Peptides Using Random Forest. Frontiers in pharmacology. 9:276.
■ (2018) Arne Elofsson, Keehyoung Joo, Chen Keasar, Jooyoung Lee, Ali H A Maghrabi, Balachandran Manavalan, Liam J McGuffin, David Ménendez Hurtado, Claudio Mirabello, Robert Pilstål, Tomer Sidi, Karolis Uziela, Björn Wallner. Methods for estimation of model accuracy in CASP12. Proteins. 86
■ (2018) Balachandran Manavalan, Rajiv Gandhi Govindaraj, Tae Hwan Shin, Myeong Ok Kim, Gwang Lee. iBCE-EL: A New Ensemble Learning Framework for Improved Linear B-Cell Epitope Prediction. Frontiers in Immunology. 9:1695
■ (2018) Balachandran Manavalan, Tae Hwan Shin, Myeong Ok Kim, Gwang Lee. PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions. Frontiers in Immunology. 9:1783
■ (2017) Balachandran Manavalan, Shaherin Basith, Tae Hwan Shin, Sun Choi, Myeong Ok Kim, Gwang Lee. MLACP: machine-learning-based prediction of anticancer peptides. Oncotarget. 8(44):77121-77136
■ (2017) Balachandran Manavalan, Jooyoung Lee. SVMQA: support-vector-machine-based protein single-model quality assessment. Bioinformatics. 33(16):2496-2503
■ (2017) Balachandran Manavalan, Tae Hwan Shin, Gwang Lee. DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest. Oncotarget. 9(2):1944-1956"
⑥ 대표전화 : 031-299-4858
⑦ 위치 : 생명공학관 62동 1층 62105호