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HaJeung Park Tuan Tran Jun Hyuck Lee Hyun Park Matthew D. Disney 《BMC structural biology》2016,16(1):19
Background
Post-crystallization dehydration methods, applying either vapor diffusion or humidity control devices, have been widely used to improve the diffraction quality of protein crystals. Despite the fact that RNA crystals tend to diffract poorly, there is a dearth of reports on the application of dehydration methods to improve the diffraction quality of RNA crystals.Results
We use dehydration techniques with a Free Mounting System (FMS, a humidity control device) to recover the poor diffraction quality of RNA crystals. These approaches were applied to RNA constructs that model various RNA-mediated repeat expansion disorders.Conclusion
The method we describe herein could serve as a general tool to improve diffraction quality of RNA crystals to facilitate structure determinations.3.
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Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction 总被引:1,自引:0,他引:1
Background
RNA secondary structure prediction methods based on probabilistic modeling can be developed using stochastic context-free grammars (SCFGs). Such methods can readily combine different sources of information that can be expressed probabilistically, such as an evolutionary model of comparative RNA sequence analysis and a biophysical model of structure plausibility. However, the number of free parameters in an integrated model for consensus RNA structure prediction can become untenable if the underlying SCFG design is too complex. Thus a key question is, what small, simple SCFG designs perform best for RNA secondary structure prediction?Results
Nine different small SCFGs were implemented to explore the tradeoffs between model complexity and prediction accuracy. Each model was tested for single sequence structure prediction accuracy on a benchmark set of RNA secondary structures.Conclusions
Four SCFG designs had prediction accuracies near the performance of current energy minimization programs. One of these designs, introduced by Knudsen and Hein in their PFOLD algorithm, has only 21 free parameters and is significantly simpler than the others.7.
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Background
Human cancers are complex ecosystems composed of cells with distinct molecular signatures. Such intratumoral heterogeneity poses a major challenge to cancer diagnosis and treatment. Recent advancements of single-cell techniques such as scRNA-seq have brought unprecedented insights into cellular heterogeneity. Subsequently, a challenging computational problem is to cluster high dimensional noisy datasets with substantially fewer cells than the number of genes.Methods
In this paper, we introduced a consensus clustering framework conCluster, for cancer subtype identification from single-cell RNA-seq data. Using an ensemble strategy, conCluster fuses multiple basic partitions to consensus clusters.Results
Applied to real cancer scRNA-seq datasets, conCluster can more accurately detect cancer subtypes than the widely used scRNA-seq clustering methods. Further, we conducted co-expression network analysis for the identified melanoma subtypes.Conclusions
Our analysis demonstrates that these subtypes exhibit distinct gene co-expression networks and significant gene sets with different functional enrichment.11.
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Background
The rate at which fitness declines as an organism's genome accumulates random mutations is an important variable in several evolutionary theories. At an intuitive level, it might seem natural that random mutations should tend to interact synergistically, such that the rate of mean fitness decline accelerates as the number of random mutations is increased. However, in a number of recent studies, a prevalence of antagonistic epistasis (the tendency of multiple mutations to have a mitigating rather than reinforcing effect) has been observed.Results
We studied in silico the net amount and form of epistatic interactions in RNA secondary structure folding by measuring the fraction of neutral mutants as a function of mutational distance d. We found a clear prevalence of antagonistic epistasis in RNA secondary structure folding. By relating the fraction of neutral mutants at distance d to the average neutrality at distance d, we showed that this prevalence derives from the existence of many compensatory mutations at larger mutational distances.Conclusions
Our findings imply that the average direction of epistasis in simple fitness landscapes is directly related to the density with which fitness peaks are distributed in these landscapes.16.
Mary Qu Yang Sherman M. Weissman William Yang Jialing Zhang Allon Canaann Renchu Guan 《BMC systems biology》2018,12(7):114
Background
Single-cell RNA sequencing (scRNA-seq) technology provides an effective way to study cell heterogeneity. However, due to the low capture efficiency and stochastic gene expression, scRNA-seq data often contains a high percentage of missing values. It has been showed that the missing rate can reach approximately 30% even after noise reduction. To accurately recover missing values in scRNA-seq data, we need to know where the missing data is; how much data is missing; and what are the values of these data.Methods
To solve these three problems, we propose a novel model with a hybrid machine learning method, namely, missing imputation for single-cell RNA-seq (MISC). To solve the first problem, we transformed it to a binary classification problem on the RNA-seq expression matrix. Then, for the second problem, we searched for the intersection of the classification results, zero-inflated model and false negative model results. Finally, we used the regression model to recover the data in the missing elements.Results
We compared the raw data without imputation, the mean-smooth neighbor cell trajectory, MISC on chronic myeloid leukemia data (CML), the primary somatosensory cortex and the hippocampal CA1 region of mouse brain cells. On the CML data, MISC discovered a trajectory branch from the CP-CML to the BC-CML, which provides direct evidence of evolution from CP to BC stem cells. On the mouse brain data, MISC clearly divides the pyramidal CA1 into different branches, and it is direct evidence of pyramidal CA1 in the subpopulations. In the meantime, with MISC, the oligodendrocyte cells became an independent group with an apparent boundary.Conclusions
Our results showed that the MISC model improved the cell type classification and could be instrumental to study cellular heterogeneity. Overall, MISC is a robust missing data imputation model for single-cell RNA-seq data.17.
Zhen Wang Jinhui Pang Bin Ji Shailin Zhang Yan Cheng Luchao Yu Weicheng Pan 《Biotechnology letters》2018,40(3):493-500
Objectives
To explore the effects of Lin28A on progression of osteocarcinoma (OS) cells.Results
Lin28A mRNA and protein expressions were significantly increased in OS tissues compared with that in normal adjacent tissues. Expressions of Lin28A and long noncoding RNA MALAT1 were positively correlated. Patients with higher Lin28A expression had shorter overall survival. Moreover, Lin28A knockdown inhibited OS cells proliferation, migration, invasion and promoted cell apoptosis; Lin28A was found to harbor binding sites on MALAT1 sequences and associated with MALAT1, and increased MALAT1 stability and expression. Notably, the inhibition of Lin28A knockdown was attenuated or even reversed by MALAT1 overexpression.Conclusions
RNA binding protein Lin28A could facilitate OS cells progression by associating with the long noncoding RNA MALAT1.18.
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