Fly and Human α-arrestin interactomes
AP/MS-based interactome maps of twelve fly and six human α-arrestins and their related Github resource.
(http://big.hanyang.ac.kr/alphaArrestin_PPIN)
Clustering with UVG
UVG: Clustering malignant cell states using universally variable genes(UVGs), which unbiased gene signatures in population-scale single-cells
(https://github.com/sangho1130/UVG)
Fly Hemocyte single-cell Atlas(FlyscRNA) v2.0
Fly scRNA-seq Database 2.0: Molecular Traces of Drosophila Hemocyte Evolution (From Fly to Human)
(http://big2.hanyang.ac.kr/flyscrna)
CINCIA
CINCIA is a meta doublet caller to infer heterotypic cell-cell interactions from single-cell RNA-seq data, which is implemented by R. You can download all source codes from
https://github.com/jwnam/CINCIA
Kim et al., In prep.
FlyscRNA
FlyscRNA is an interactive Sophia web-program (deployed from Seurat) to visualize scRNA-seq data from fly lymph gland in three larvae stages.
http://big.hanyang.ac.kr/flyscrna
Cho et al., Nature Comm., 11:4483, 2020
DGD
DGD is a new DL method for the optimal design of single guide RNAs (sgRNAs) by taking account of the secondary structure of sgRNAs. DGD is outperforming the current state-of-art AI methods.
https://github.com/GuideDesigner/DGD-Cas9
Vipin et al, in prep.
ETCHING
ETCHING is the fastest somatic SV and fusion gene caller that utilizes pan-genome k-mer set
http://big.hanyang.ac.kr/ETCHING
Sohn, Choi, and Yi et al., Nature Biomed. Eng. 7, 853–866, 2023.
CGD
A comprehensive guide designer for CRISPR systems. The CGD is a predictive regression models that predict efficient gRNAs for CRISPRi, CRISPRa, Cas9, Cas12a in a comprehensive manner.
http://big.hanyang.ac.kr:2195/CGD
Menon et al., CSBJ, 18:814-820, 2020.
CINDEL
A regression-based model for CRISPR AsCpf1 Indel score, trained with hundreds of in-vitro datasets that Prof. Hyungbum Kim's lab generated.
http://big.hanyang.ac.kr/cindel/
Kim et al., Nature Methods, 14:153–159, 2017.
CANDL
CANDL is a comprehensive liver cancer database built by BIG Lab. It currently integrates microarray, RNA-seq, sRNA-seq data from Korean and TCGA liver cancer samples. Users can easily get information about gene expression level changes and how each sample correlates with another. CANDL also provides a simple one-step analysis of DEG analysis between selected group of samples.
(http://big.hanyang.ac.kr/CANDL/)
TERIUS
ERIUS provides a two-step filtration process to distinguish between bona fide and false lncRNAs. The first step successfully separates lncRNAs from protein-coding genes with low ribosome signals, showing enhanced sensitivity compared to other methods. To eliminate 3’UTR fragments, the second step takes advantage of the 3’UTR-specific association with regulator of nonsense transcripts 1, leading to refined lncRNA annotation.
(https://bigterius.wordpress.com/)
Choi et al., BMC Bioinformatics, 19(Suppl 1):41, 2018.
CAFE
description: We present a high-performing transcriptome assembly pipeline, called CAFE (Co-Assembly of stranded and unstranded RNA-seq data Followed by End-correction), that significantly improves the original assemblies, respectively assembled with stranded and/or unstranded RNA-seq data, by orienting unstranded reads using the maximum likelihood estimation and by integrating information about transcription start sites and cleavage and polyadenylation sites.
You et al., Genome Res. 27(6):1050-1062, 2017.
CASOL
Comprehensive Annotation System Of mammalian LncRNAs, is a web program that (1) reconstructs transcriptomes from multi-modal transcriptomic data, such as RNA-seq, PolyA-seq, and DeepCAGE, and (2) classifies lncRNAs from protein-coding genes using orthologous classifiers: CPC, RPS, RRS, TE.
In this site, we have improved published lncRNA annotations and catalogue reference set of mammalian lncRNAs, identified from CASOL system.
LINDEL
LINDEL is the Integrated Design system for LincRNA deletion (LINDEL) , which was implemented on an interactive web genome-browser. (http://big.hanyang.ac.kr/LINDEL)
Lee et al., NAR, 47:8, 3875–3887, 2019.
GETUTR
GETUTR is global estimation of the 3’ UTR landscape based on RNA sequencing. The main purpose of GETUTR is to smooth fluctuating RNA-seq signals to estimate a monotonically decreasing landscape of 3’ UTRs. The three smoothing algorithms of GETUTR were incorpoated: Minfit, Maxfit, and PAVA. Using GETUTR, the dynamic changes of 3’ UTR usage can be quantified in any cell type, stage, and species for which RNA-seq data are available, thereby leading to a better understanding of 3’ UTR biology.
Kim et al., Methods, 83:111-117. 2015.
miTarget (under construction)
miTarget is a support vector machine (SVM) classifier for miRNA target gene prediction. It uses a radial basis function kernel as a similarity measure for SVM features, categorized by structural, thermodynamic, and position-based features.
Kim et al., 7:411, BMC Bionformatics, 2006.
ProMiR2 (under construction)
ProMiR is a web-based service for the prediction of potential microRNAs(miRNAs) in a querysequence of 60–150 nt, using a probabilistic colearning model. Identification of miRNAs requires a computational method to predict clustered and nonclustered, conserved and nonconserved miRNAs in various species.
Nam et al., Webserver issue Vol34, NAR, 2006.
Nam et al., 33:11 3570–3581, NAR, 2005.