• Molecules and Cells
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• v.42 no.3
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• pp.189-199
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• 2019

Cell-to-cell variability in gene expression exists even in a homogeneous population of cells. Dissecting such cellular heterogeneity within a biological system is a prerequisite for understanding how a biological system is developed, homeostatically regulated, and responds to external perturbations. Single-cell RNA sequencing (scRNA-seq) allows the quantitative and unbiased characterization of cellular heterogeneity by providing genome-wide molecular profiles from tens of thousands of individual cells. A major question in analyzing scRNA-seq data is how to account for the observed cell-to-cell variability. In this review, we provide an overview of scRNA-seq protocols, computational approaches for dissecting cellular heterogeneity, and future directions of single-cell transcriptomic analysis.

• Genomics & Informatics
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• v.19 no.4
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• pp.51.1-51.8
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• 2021

This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bioinformatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were reviewed. Content analysis was the main method employed in the current research. The results were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.313-318
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• 2005

Estimating the reliability of protein-protein interaction data sets obtained by high-throughput technologies such as yeast two-hybrid assays and mass spectrometry is of great importance. We develop a maximum likelihood estimation method that uses both protein localization and gene expression data to estimate the reliability of protein interaction data sets. By integrating protein localization data and gene expression data, we can obtain more accurate estimates of the reliability of various interaction data sets. We apply the method to protein physical interaction data sets and protein complex data sets. The reliability of the yeast two-hybrid interactions by Ito et al. (2001) is 27%, and that by Uetz et at.(2000) is 68%. The reliability of the protein complex data sets using tandem affinity purification-mass spec-trometry (TAP) by Gavin et at. (2002) is 45%, and that using high-throughput mass spectrometric protein complex identification (HMS-PCI) by Ho et al. (2002) is 20%. The method is general and can be applied to analyze any protein interaction data sets.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.287-293
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• 2005

Predicting RNA secondary structure as accurately as possible is very important in functional analysis of RNA molecules. However, different prediction methods and related parameters including terminal GU pair of helices, minimum length of helices, and free energy systems often give different prediction results for the same RNA sequence. Then, which structure is more important than the others? i.e. which combinations of the methods and related parameters are the optimal? In order to investigate above problems, first, three prediction methods, namely, random stacking of helical regions (RS), helical regions distribution (HD), and Zuker's minimum free energy algorithm (ZMFE) were compared by taking 1139 tRNA sequences from Rfam database as the samples with different combinations of parameters. The optimal parameters are derived. Second, Zuker's dynamic programming method for prediction of RNA secondary structure was revised using the above optimal parameters and related software BJRNAFold was developed. Third, the effects of short-range interaction were studied. The results indicated that the prediction accuracy would be improved much if proper short-range factor were introduced. But the optimal short-range factor was difficult to determine. A user-adjustable parameter for short-range factor was introduced in BJRNAFold software.

• Mycobiology
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• v.48 no.1
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• pp.58-69
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• 2020

Meghalaya, (in India), in the region of the mega-biodiversity hotspots, is home to a plethora of wild mushrooms. The present study concerns the exploration of the order Agaricales, which includes rare gilled mushrooms considered endangered under IUCN A4c criteria, due to the declining habitat. Electron microscopy of the gill sections revealed an abundance of clamp connections, hyphal cell walls, cystidia, and basidia. This rare species which belongs to the family Cyphellaceae, exhibits morphological and molecular differences from the Cyphella spp. Phylogenetic analysis revealed that it formed a clade under the genus Campanophyllum of the order Agaricales, confirmed by both Neighbor Joining (NJ) and Bayesian phylogenetic analysis. Being nutritionally potent along with its efficient antioxidant value, the fungal extract shows significant rise of two-fold in the antimicrobial activity along with the commercial antibiotics. The compound, Phenol, 2, 4-bis (1, 1-Dimethylethyl) (2, 4-DTBP) showed in ample range in the fungal extract along with aliphatic hydrocarbons, terpene, alcohol and volatile organic compounds on further characterization in GCMS. The present study indicates the endangered Campanophyllum proboscideum could be a rich source of natural antioxidants and an effective pharmaceutical agent.

• Genomics & Informatics
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• v.11 no.3
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• pp.155-160
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• 2013

Structural information has been a major concern for biological and pharmaceutical studies for its intimate relationship to the function of a protein. Three-dimensional representation of the positions of protein atoms is utilized among many structural information repositories that have been published. The reliability of the torsional system, which represents the native processes of structural change in the structural analysis, was partially proven with previous structural alignment studies. Here, a web server providing structural information and analysis based on the backbone torsional representation of a protein structure is newly introduced. The web server offers functions of secondary structure database search, secondary structure calculation, and pair-wise protein structure comparison, based on a backbone torsion angle representation system. Application of the implementation in pair-wise structural alignment showed highly accurate results. The information derived from this web server might be further utilized in the field of ab initio protein structure modeling or protein homology-related analyses.

• Genomics & Informatics
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• v.9 no.2
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• pp.74-78
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• 2011

Numerous restraints and simplifications have been developed for methods that anticipate protein structure to reduce the colossal magnitude of possible conformational states. In this study, we investigated if globularity is a general characteristic of proteins and whether they can be applied as a valid constraint in protein structure simulations with approximated measurements (Gb-index). Unexpectedly, most of the proteins showed strong structural globularity (i.e., mode of approximately 76% similarity to the perfect globe) with only a few percent of proteins being outliers. Small proteins tended to be significantly non-globular ($R^2$=0.79) and the minimum Gb-index showed a logarithmic increase with the increase in protein size ($R^2$=0.62), strongly implying that the non-globular characteristics might be more acceptable for smaller proteins than larger ones. The strong perfect globe-like character and the relationship between small size and the loss of globular structure of a protein may imply that living organisms have mechanisms to aid folding into the globular structure to reduce irreversible aggregation. This also implies the possible mechanisms of diseases caused by protein aggregation, including some forms of trinucleotide repeat expansion-mediated diseases.

• International Journal of CAD/CAM
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• v.7 no.1
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• pp.91-101
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• 2007

To understand the structure of molecules, various computational methodologies have been extensively investigated such as the Voronoi diagram of the centers of atoms in molecule and the power diagram for the weighted points where the weights are related to the radii of the atoms. For a more improved efficiency, constructs like an $\alpha$-shape or a weighted $\alpha$-shape have been developed and used frequently in a systematic analysis of the morphology of molecules. However, it has been recently shown that $\alpha$-shapes and weighted $\alpha$-shapes lack the fidelity to Euclidean distance for molecules with polysized spherical atoms. We present the theory as well as algorithms of $\beta$-shape and $\beta$-complex in $\mathbb{R}^3$ which reflects the size difference among atoms in their full Euclidean metric. We show that these new concepts are more natural for most applications and therefore will have a significant impact on applications based on particles, in particular in molecular biology. The theory will be equivalently useful for other application areas such as computer graphics, geometric modeling, chemistry, physics, and material science.

• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.185-190
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• 2007

Objectives : Since the first human infection from avian influenza was reported in Hong Kong in 1997, many Asian countries have confirmed outbreaks of highly pathogenic H5N1 avian influenza viruses. In addition to Asian countries, the EU authorities also held an urgent meeting in February 2006 at which it was agreed that Europe could also become the next target for H5N1 avian influenza in the near future. In this paper, we provide the general and applicable information on the avian influenza in the bioinformatics field to assist future studies in preventive medicine. Methods : We introduced some up-to-date analytical tools in bioinformatics research, and discussed the current trends of avian influenza outbreaks. Among the bioinformatics methods, we focused our interests on two topics: pattern analysis using the secondary database of avian influenza, and structural analysis using the molecular dynamics simulations in vaccine design. Results : Use of the public genome databases available in the bioinformatics field enabled intensive analysis of the genetic patterns. Moreover, molecular dynamic simulations have also undergone remarkable development on the basis of the high performance supercomputing infrastructure these days. Conclusions : The bioinformatics techniques we introduced in this study may be useful in preventive medicine, especially in vaccine and drug discovery.

• Journal of Integrative Natural Science
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• v.15 no.4
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• pp.145-152
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• 2022

Colon rectal cancer is one of the frequently diagnosed cancers worldwide. In recent times the drug discovery for colon cancer is challenging because of their speedy metastasis and morality of these patients. C-jun N-terminal kinase signaling pathway controls the cell cycle survival and apoptosis. Evidence has shown that JNK1 promotes the tumor progression in various types of cancers like colon cancer, breast cancer and lung cancer. Recent study has shown that inhibiting, JNK1 pathway is identified as one of the important cascades in drug discovery. One of the recent approaches in the field of drug discovery is drug repurposing. In drug repurposing approach we have virtually screened ChEMBL dataset against JNK1 protein and their interactions have been studied through Molecular docking. Cross docking was performed with the top compounds to be more specific with JNK1 comparing the affinity with JNK2 and JNK3.The drugs which exhibited higher binding were subjected to Conceptual - Density functional theory. The results showed mainly Entrectinib and Exatecan showed better binding to the target.