1,722,744 research outputs found
SAM Filtering Pipeline (SFP): Algorithm for the determination of integration sites from next generation sequencing data
No full textThe locus at which a vector harboring a product transgene integrates into the genome can have a profound effect on the transgene’s transcript level and the stability of the resulting cell line. In order to identify integration site(s) of a transfected vector from next generation genome sequencing data, the SAM filtering pipeline (SFP) was created. It is best suited for targeted sequence data, such as that from sequence capture of probed vector regions. However, it will also work for whole genome sequencing data, though the memory requirements are large (the more reads in your data set, the larger the memory requirements). A bwa-mem mapped .sam file is required as input to the pipeline.O'Brien, Sofie A; Hu, Wei-Shou. (2019). SAM Filtering Pipeline (SFP): Algorithm for the determination of integration sites from next generation sequencing data. Retrieved from the University Digital Conservancy, https://doi.org/10.13020/9wgm-mj51
A mechanistic-empirical model of central metabolism, signaling, and the reactor environment for bioprocesses
No full textThis model was built and optimized to reproduce the variability inherent to many industrial cell-culture processes. Classically, fed-batch Chinese Hamster Ovary (CHO) cell cultures will initially produce lactate in the early phase of culture before switching to lactate consumption. However, some processes may revert to lactate production in the late stage of culture, driving up osmolarity while reducing viable cell density, and ultimately lowering process performance. This phenomenon may occur in only some runs of a manufacturing processes and even may differ among runs with similar initial conditions and trajectories, leading to longstanding questions about the mechanisms driving this switch. By simulating cultures which were exposed to different amounts of stress before the production bioreactor we show that similar starting conditions in the bioreactor environment can lead to variability in metabolic shift. We provide this model as a tool to demonstrate this metabolic variability and provide a platform for hypothesis testing, in silico bioprocess optimization, and simulation of reactor scale-up and scale-down.O'Brien, Conor M; Hu, Wei-Shou. (2020). A mechanistic-empirical model of central metabolism, signaling, and the reactor environment for bioprocesses. Retrieved from the University Digital Conservancy, https://doi.org/10.13020/kdqb-3023
GlycoVis: Visualizing Glycan Distribution in the Protein N-Glycosylation Pathwayin Mammalian Cells
No full textGlycosylation pattern is an important quality attribute of protein therapeutics. It affects protein stability, half-life and even biological functions. The N-glycosylation pathway is a highly branched network. Although only a relative small number of enzymes involved in the pathway, a multitude of glycan intermediates can be produced. In order to study this network, GlycoVis was created to visualize the distribution of glycans and potential reaction paths leading to each glycan in the N-glycosylation network. The program was written in Matlab, interfacing with Graphviz. It incorporates substrate specificity of the enzymes involved in the pathway in a relationship matrix. Given an input of glycan distribution data, the program traces all the potential reaction paths leading to each glycan, and outputs pathway maps with glycans colored in line with their relative abundances.Hossler, Patrick; Hu, Wei-Shou. (2016). GlycoVis: Visualizing Glycan Distribution in the Protein N-Glycosylation Pathwayin Mammalian Cells. Retrieved from the University Digital Conservancy, http://doi.org/10.13020/D6GP45
Regions of High Confidence in Chinese Hamster and CHO-K1 Genome Assemblies
No full textTo assess the quality of the genome assembly, a comparison was done between a publically available AMDS00000000.1 draft assembly of Chinese hamster genome with in-house UMN1.0 to mark consensus regions on the former draft assembly. Using a stringent criterion of contiguous segments larger than 1 Kbp with sequence identity greater than 97 % matching to unique reference and query sequence, 82 % of the total scaffold length consists of consensus regions with the UMN1.0. Since these regions are conserved across two independent assemblies, they are highly likely to have been assembled correctly. Similar analysis was done to compare the CHO-K1 (AFTD00000000.1) and Chinese hamster genome (AMDS00000000.1). Using the above-mentioned criteria 1.72 Gbp (71.9 %) of CHO-K1 genome can be identified as 'high confidence regions'. These regions of consensus were compiled in a bed file containing the scaffold ID, start and end positions of the 'high confidence regions' is available in this data set.Chinese hamster Ovary (CHO) cell lines are the dominant industrial workhorses for therapeutic recombinant protein production. The availability of the genome sequence of Chinese hamster and CHO cells will spur further genome and RNA sequencing of producing cell lines. However, the mammalian genomes assembled using shot-gun sequencing data still contain regions of uncertain quality due to assembly errors. Identifying high confidence regions in the assembled genome will facilitate its use for cell engineering and genome engineering. This dataset includes two genome annotation files that identify the 'high confidence regions' shared by the genome assemblies in comparison. The potential use of these files are to find locations in the publically available genome which are likely to be assembled correctly. These regions can be used confidently for genome engineering.Vishwanathan, Nandita; Bandyopadhyay, Arpan; Fu, Hsu-Yuan; Sharma, Mohit; Johnson, Kathryn; Mudge, Joann; Ramaraj, Thiruvarangan; Onsongo, Getiria; Silverstein, Kevin A. T.; Jacob, Nitya M.; Le, Huong; Karypis, George; Hu, Wei-Shou. (2016). Regions of High Confidence in Chinese Hamster and CHO-K1 Genome Assemblies. Retrieved from the University Digital Conservancy, http://dx.doi.org/10.13020/D6Z304
Yi tu ming bian: [10 juan]. v.36
No full text胡渭撰 ; [伍崇曜輯]Date from preface.框13.1 x 9.1 cm., 9行21字, 黑口, 左右雙邊, 無魚尾, 版心中鐫分冊書名, 下鐫叢書名.Hu Wei zhuan; [Wu Chongyao ji]Kuang 13.1 x 9.1 cm., 9 xing 21 zi, hei kou, zuo you shuang bian, wu yu wei, ban xin zhong juan fen ce shu ming, xia juan cong shu ming
How followers' unethical behavior is triggered by leader-member exchange: The mediating effect of job satisfaction
No full textIn previous studies (see e.g., Liden, Sparrowe, & Wayne, 1997; Schyns & Croon, 2006; Volmer, Niessen, Spurk, Linz, & Abele, 2011), leader-member exchange (LMX) has been shown to be related to positive outcomes. However, little attention has been paid to the relationship between LMX and negative organizational behaviors such as unethical behavior. In this study we investigated 249 Chinese managers in 4 different finance companies in China, and found that there is a mediating effect of job satisfaction on the negative relationship between LMX and unethical behavior
Some improved Razumikhin stability criteria for impulsive stochastic delay differential systems
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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