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ENSEMBL Special: The Ensembl Analysis Pipeline
- Simon C. Potter,
- Laura Clarke,
- Val Curwen,
- Stephen Keenan,
- Emmanuel Mongin,
- Stephen M.J. Searle,
- Arne Stabenau,
- Roy Storey,
- and Michele Clamp
Genome Res. May 2004 14: 934-941; doi:10.1101/gr.1859804
...: In this window In a new window Figure 1 Ensembl pipeline system overview: The RuleManager uses LSF to submit analysis jobs to the compute farm. When an individual job starts executing on a remote node, the Runner script fetches the job information from the database and recreates the Job object. This in turn...
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ENSEMBL Special: The Ensembl Automatic Gene Annotation System
- Val Curwen,
- Eduardo Eyras,
- T. Daniel Andrews,
- Laura Clarke,
- Emmanuel Mongin,
- Steven M.J. Searle,
- and Michele Clamp
Genome Res. May 2004 14: 942-950; doi:10.1101/gr.1858004
...of the current Ensembl gene build is given in Figure 1 . View larger version: In this window In a new window Figure 1 Overview of Ensembl Gene Build. Most genes are predicted using the sequences of known proteins aligned to the using genewise (Targetted and Similarity builds). UTR sequences for these genes...
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ENSEMBL Special: The Ensembl Web Site: Mechanics of a Genome Browser
- James Stalker,
- Brian Gibbins,
- Patrick Meidl,
- James Smith,
- William Spooner,
- Hans-Rudolf Hotz,
- and Antony V. Cox
Genome Res. May 2004 14: 951-955; doi:10.1101/gr.1863004
...become a truism that the body of data associated with s is large and ever increasing. It has also become evident that this plethora of data can make it difficult to access specific pieces of information, get a high-level overview of data, or examine data patterns. Ensembl is one of several systems...
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Method: EnDeep4mC predicts DNA N⁴-methylcytosine sites using a dual-adaptive feature encoding framework in deep ensembles
- Shuyu Zhang,
- Quan Zou,
- Mengting Niu,
- Zhibin Lv,
- Antony Stalin,
- and Ximei Luo
Genome Res. March 2026 36: 589-599; Published in Advance February 17, 2026, doi:10.1101/gr.280977.125
...species-specific modeling with ensemble deep learning architectures to systematically optimize feature encoding schemes. Evaluated across six species, EnDeep4mC demonstrates commendable prediction performance and significantly outperforms current state-of-the-art predictors. Cross-species validation...
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Method: Scalable cell-specific coexpression networks for granular regulatory pattern discovery with NeighbourNet
- Yidi Deng,
- Jiadong Mao,
- Jarny Choi,
- and Kim-Anh Lê Cao
Genome Res. April 2026 36: 785-801; Published in Advance March 5, 2026, doi:10.1101/gr.281171.125
...integration to facilitate cell-specific inference of active gene regulation and upstream signaling pathways (USPs). NNet, along with its downstream analysis modules, are available as an R package that integrates seamlessly with the widely used Seurat pipeline.ResultsOverview of NNetWe begin by outlining...
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Resource: The SynMall resource for characterizing the functional impact of synonymous variation
- Chen Ye,
- Xiaoyan Li,
- Na Cheng,
- Yansen Su,
- and Junfeng Xia
Genome Res. February 2026 36: 421-431; Published in Advance December 17, 2025, doi:10.1101/gr.281257.125
...research into the role of sSNVs.ResultsOverview of SynMallSynMall is a -wide platform for sSNVs that provides comprehensive characterization and supports both biological and computational studies. As shown in Figure 1A, first, SynMall identifies all potential sSNVs on protein-coding transcripts...
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Method: Simultaneous modeling of chromatin conformation changes from multiple single-cell interaction maps with ChromMovie
- Krzysztof H. Banecki,
- Haoxi Chai,
- Yijun Ruan,
- and Dariusz Plewczynski
Genome Res. April 8, 2026 ; Published in Advance April 8, 2026, doi:10.1101/gr.280985.125
...). Notable examples of Hi-C–based methods successfully applied to the study of chromatin structure changes during cellular processes are maximum entropy models. By generating ensembles of structures, these approaches are able to reproduce ensemble-level chromatin behavior and contact distributions...
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Method: Automated interpretable artificial intelligence genomic prediction with AIGP
- Lei Wei,
- Ziqin Jiang,
- Baoliang Fan,
- Yidan Yan,
- Zhenqiang Xu,
- Xiaoxiang Hu,
- and Yuzhe Wang
Genome Res. April 2026 36: 814-826; Published in Advance March 5, 2026, doi:10.1101/gr.281006.125
...of the genetic architecture. (A) Overview of the analytical framework. Phenotypic and genomic data from four species (pig, chicken, horse, and maize) were used to estimate heritability and genetic variance components, and a -wide association study (GWAS) was conducted to identify significant quantitative trait...
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Method: Highly accurate reference and method selection for universal cross–data set cell type annotation with CAMUS
- Qunlun Shen,
- Shuqin Zhang,
- and Shihua Zhang
Genome Res. November 2025 35: 2527-2538; Published in Advance October 1, 2025, doi:10.1101/gr.280821.125
...to this metric as the CAMUS score.ResultsOverview of CAMUSCAMUS aims to prioritize reference–method pairs and select the optimal one, ensuring the highest accuracy for a reference-based single-cell annotation task. CAMUS utilizes the single-cell expression profiles from the query data and the annotation results...
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Method: Parallel analysis of replication timing, gene expression, and copy number with PARTAGE
- Lakshana Sruthi Sadu Murari,
- Quinn Dickinson,
- Silvia Meyer-Nava,
- and Juan Carlos Rivera-Mulia
Genome Res. April 2026 36: 802-813; Published in Advance March 19, 2026, doi:10.1101/gr.281532.125
...-Mulia and Gilbert 2016b; Vouzas and Gilbert 2023). One limitation is the lack of methods enabling the simultaneous measurement of RT and gene expression from the same samples. Although multiple RT profiling methods exist at the ensemble population level (Marchal et al. 2018; Hulke et al. 2020; Rivera-Mulia et al...
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