| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
Algorithmic approaches to clonal reconstruction in heterogeneous cell populations
|
Ismail, Wazim Mohammed
|
|
|
|
4 |
p. 255-265
|
artikel
|
| 2 |
Algorithmic approaches to clonal reconstruction in heterogeneous cell populations
|
Ismail, Wazim Mohammed
|
|
|
|
4 |
p. 255-265
|
artikel
|
| 3 |
Analysis of protein features and machine learning algorithms for prediction of druggable proteins
|
Sun, Tanlin
|
|
2018
|
|
4 |
p. 334-343
|
artikel
|
| 4 |
Applications of integrative OMICs approaches to gene regulation studies
|
Qin, Jing
|
|
2016
|
|
4 |
p. 283-301
|
artikel
|
| 5 |
A resistant method for landmark-based analysis of individual asymmetry in two dimensions
|
Torcida, Sebastián
|
|
2016
|
|
4 |
p. 270-282
|
artikel
|
| 6 |
A survey of some tensor analysis techniques for biological systems
|
Yahyanejad, Farzane
|
|
|
|
4 |
p. 266-277
|
artikel
|
| 7 |
A survey of some tensor analysis techniques for biological systems
|
Yahyanejad, Farzane
|
|
|
|
4 |
p. 266-277
|
artikel
|
| 8 |
A survey on biomarker identification based on molecular networks
|
Zhu, Guanghui
|
|
2016
|
|
4 |
p. 310-319
|
artikel
|
| 9 |
Cap-seq reveals complicated miRNA transcriptional mechanisms in C. elegans and mouse
|
Chen, Jiao
|
|
2017
|
|
4 |
p. 352-367
|
artikel
|
| 10 |
Characterizing robustness and sensitivity of convolutional neural networks for quantitative analysis of mitochondrial morphology
|
Chai, Xiaoqi
|
|
2018
|
|
4 |
p. 344-358
|
artikel
|
| 11 |
Collective motion of bacteria in two dimensions
|
Wu, Yilin
|
|
2015
|
|
4 |
p. 199-205
|
artikel
|
| 12 |
Computational inference of physical spatial organization of eukaryotic genomes
|
Xu, Bingxiang
|
|
2016
|
|
4 |
p. 302-309
|
artikel
|
| 13 |
Constructing a Boolean implication network to study the interactions between environmental factors and OTUs
|
Zhu, Congmin
|
|
2014
|
|
4 |
p. 127-141
|
artikel
|
| 14 |
Construction, visualization, and analysis of biological network models in Dynetica
|
Eidum, Derek
|
|
2014
|
|
4 |
p. 142-150
|
artikel
|
| 15 |
Differential expression analyses for single-cell RNA-Seq: old questions on new data
|
Miao, Zhun
|
|
2016
|
|
4 |
p. 243-260
|
artikel
|
| 16 |
Differential methylation analysis for bisulfite sequencing using DSS
|
Feng, Hao
|
|
|
|
4 |
p. 327-334
|
artikel
|
| 17 |
Differential methylation analysis for bisulfite sequencing using DSS
|
Feng, Hao
|
|
|
|
4 |
p. 327-334
|
artikel
|
| 18 |
Emerging deep learning methods for single-cell RNA-seq data analysis
|
Zheng, Jie
|
|
|
|
4 |
p. 247-254
|
artikel
|
| 19 |
Emerging deep learning methods for single-cell RNA-seq data analysis
|
Zheng, Jie
|
|
|
|
4 |
p. 247-254
|
artikel
|
| 20 |
Experimental design and model reduction in systems biology
|
Jeong, Jenny E.
|
|
2018
|
|
4 |
p. 287-306
|
artikel
|
| 21 |
Generic properties of random gene regulatory networks
|
Li, Zhiyuan
|
|
2013
|
|
4 |
p. 253-260
|
artikel
|
| 22 |
Generic properties of random gene regulatory networks
|
Li, Zhiyuan
|
|
2014
|
|
4 |
p. 253-260
|
artikel
|
| 23 |
Identifying patient-specific flow of signal transduction perturbed by multiple single-nucleotide alterations
|
Kholod, Olha
|
|
|
|
4 |
p. 336-346
|
artikel
|
| 24 |
Imaging genetics — towards discovery neuroscience
|
Ge, Tian
|
|
2013
|
|
4 |
p. 227-245
|
artikel
|
| 25 |
Imaging genetics — towards discovery neuroscience
|
Ge, Tian
|
|
2014
|
|
4 |
p. 227-245
|
artikel
|
| 26 |
IRIS: A method for predicting in vivo RNA secondary structures using PARIS data
|
Zhou, Jianyu
|
|
|
|
4 |
p. 369-381
|
artikel
|
| 27 |
Mathematical approaches in studying bicoid gene
|
Ghodsi, Zara
|
|
2015
|
|
4 |
p. 182-192
|
artikel
|
| 28 |
Meeting report on Synthetic Biology Young Scholar Forum
|
Xie, Zhen
|
|
2015
|
|
4 |
p. 206-211
|
artikel
|
| 29 |
Microfluidics and its applications in quantitative biology
|
Tu, Yuhai
|
|
2013
|
|
4 |
p. 272-280
|
artikel
|
| 30 |
Microfluidics and its applications in quantitative biology
|
Tu, Yuhai
|
|
2014
|
|
4 |
p. 272-280
|
artikel
|
| 31 |
Molecular modeling studies of repandusinic acid as potent small molecule for hepatitis B virus through molecular docking and ADME analysis
|
Subramaniyan, Vijayakumar
|
|
|
|
4 |
p. 302-312
|
artikel
|
| 32 |
Molecular modeling studies of repandusinic acid as potent small molecule for hepatitis B virus through molecular docking and ADME analysis
|
Subramaniyan, Vijayakumar
|
|
|
|
4 |
p. 302-312
|
artikel
|
| 33 |
Multi-chain Fudan-CCDC model for COVID-19—a revisit to Singapore’s case
|
Pan, Hanshuang
|
|
|
|
4 |
p. 325-335
|
artikel
|
| 34 |
NAD+ and its precursors in human longevity
|
Lin, Jimin
|
|
2015
|
|
4 |
p. 193-198
|
artikel
|
| 35 |
NPEST: a nonparametric method and a database for transcription start site prediction
|
Tatarinova, Tatiana
|
|
2013
|
|
4 |
p. 261-271
|
artikel
|
| 36 |
NPEST: a nonparametric method and a database for transcription start site prediction
|
Tatarinova, Tatiana
|
|
2014
|
|
4 |
p. 261-271
|
artikel
|
| 37 |
On statistical energy functions for biomolecular modeling and design
|
Liu, Haiyan
|
|
2015
|
|
4 |
p. 157-167
|
artikel
|
| 38 |
On the possibility of identifying human subjects using behavioural complexity analyses
|
Kloucek, Petr
|
|
2016
|
|
4 |
p. 261-269
|
artikel
|
| 39 |
On the statistical significance of protein complex
|
Su, Youfu
|
|
2018
|
|
4 |
p. 313-320
|
artikel
|
| 40 |
On the use of kernel machines for Mendelian randomization
|
Zhang, Weiming
|
|
2017
|
|
4 |
p. 368-379
|
artikel
|
| 41 |
Overlap graphs and de Bruijn graphs: data structures for de novo genome assembly in the big data era
|
Rizzi, Raffaella
|
|
|
|
4 |
p. 278-292
|
artikel
|
| 42 |
Overlap graphs and de Bruijn graphs: data structures for de novo genome assembly in the big data era
|
Rizzi, Raffaella
|
|
|
|
4 |
p. 278-292
|
artikel
|
| 43 |
Performance measures in evaluating machine learning based bioinformatics predictors for classifications
|
Jiao, Yasen
|
|
2016
|
|
4 |
p. 320-330
|
artikel
|
| 44 |
Performance-weighted-voting model: an ensemble machine learning method for cancer type classification using whole-exome sequencing mutation
|
Li, Yawei
|
|
|
|
4 |
p. 347-358
|
artikel
|
| 45 |
PMTDS: a computational method based on genetic interaction networks for Precision Medicine Target-Drug Selection in cancer
|
Vasudevaraja, Varshini
|
|
2017
|
|
4 |
p. 380-394
|
artikel
|
| 46 |
Prediction and analysis of human-herpes simplex virus type 1 protein-protein interactions by integrating multiple methods
|
Lian, Xianyi
|
|
|
|
4 |
p. 312-324
|
artikel
|
| 47 |
Quantitative analysis of gene expression systems
|
Zhou, Tianshou
|
|
2015
|
|
4 |
p. 168-181
|
artikel
|
| 48 |
Quantitative Biology 2019: Dynamic Signaling in Cells and Embryos
|
Liu, Feng
|
|
|
|
4 |
p. 335-337
|
artikel
|
| 49 |
Quantitative Biology 2019: Dynamic Signaling in Cells and Embryos
|
Liu, Feng
|
|
|
|
4 |
p. 335-337
|
artikel
|
| 50 |
Quantitative biology: from genes, cells to networks
|
Xie, Zhen
|
|
2014
|
|
4 |
p. 151-156
|
artikel
|
| 51 |
Recent advances and application in whole-genome multiple displacement amplification
|
Long, Naiyun
|
|
|
|
4 |
p. 279-294
|
artikel
|
| 52 |
RECOGNICER: A coarse-graining approach for identifying broad domains from ChIP-seq data
|
Zang, Chongzhi
|
|
|
|
4 |
p. 359-368
|
artikel
|
| 53 |
Selecting near-native protein structures from ab initio models using ensemble clustering
|
Li, Li
|
|
2018
|
|
4 |
p. 307-312
|
artikel
|
| 54 |
Special collection of bioinformatics in the era of precision medicine
|
Qin, Zhaohui S.
|
|
2017
|
|
4 |
p. 277-279
|
artikel
|
| 55 |
Subnetwork identification and chemical modulation for neural regeneration: A study combining network guided forest and heat diffusion model
|
Wang, Hui
|
|
2018
|
|
4 |
p. 321-333
|
artikel
|
| 56 |
Synthetic biology: a new approach to study biological pattern formation
|
Liu, Chenli
|
|
2013
|
|
4 |
p. 246-252
|
artikel
|
| 57 |
The Ontology of Biological and Clinical Statistics (OBCS)-based statistical method standardization and meta-analysis of host responses to yellow fever vaccines
|
Zheng, Jie
|
|
2017
|
|
4 |
p. 291-301
|
artikel
|
| 58 |
Toward an understanding of the relation between gene regulation and 3D genome organization
|
Tian, Hao
|
|
|
|
4 |
p. 295-311
|
artikel
|
| 59 |
Towards integrated oncogenic marker recognition through mutual information-based statistically significant feature extraction: an association rule mining based study on cancer expression and methylation profiles
|
Mallik, Saurav
|
|
2017
|
|
4 |
p. 302-327
|
artikel
|
| 60 |
Transcription regulation by DNA methylation under stressful conditions in human cancer
|
Cao, Sha
|
|
2017
|
|
4 |
p. 328-337
|
artikel
|
| 61 |
Transcriptome assembly strategies for precision medicine
|
Wang, Lu
|
|
2017
|
|
4 |
p. 280-290
|
artikel
|
| 62 |
Variable importance-weighted random forests
|
Liu, Yiyi
|
|
2017
|
|
4 |
p. 338-351
|
artikel
|
| 63 |
WaveNano: a signal-level nanopore base-caller via simultaneous prediction of nucleotide labels and move labels through bi-directional WaveNets
|
Wang, Sheng
|
|
2018
|
|
4 |
p. 359-368
|
artikel
|
| 64 |
WEDeepT3: predicting type III secreted effectors based on word embedding and deep learning
|
Fu, Xiaofeng
|
|
|
|
4 |
p. 293-301
|
artikel
|
| 65 |
WEDeepT3: predicting type III secreted effectors based on word embedding and deep learning
|
Fu, Xiaofeng
|
|
|
|
4 |
p. 293-301
|
artikel
|
| 66 |
WIPER: Weighted in-Path Edge Ranking for biomolecular association networks
|
Yue, Zongliang
|
|
|
|
4 |
p. 313-326
|
artikel
|
| 67 |
WIPER: Weighted in-Path Edge Ranking for biomolecular association networks
|
Yue, Zongliang
|
|
|
|
4 |
p. 313-326
|
artikel
|
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