bluuebunny/crossref_metadata_2025_split huggingface dataset:
Knockdown of Hspa9, a del(5q31.2) gene, results in a decrease in hematopoietic progenitors in mice
Authors: Chen Tim H.-P. , Kambal Amal , Krysiak Kilannin , Walshauser Mark A. , Raju Gagan , Tibbitts Justin F. , Walter Matthew J. 
Published: December 2010

AbstractHeterozygous deletions spanning chromosome 5q31.2 occur frequently in the myelodysplastic syndromes (MDS) and are highly associated with progression to acute myeloid leukemia (AML) when p53 is mutated. Mutagenesis screens in zebrafish and mice identified Hspa9 as a del(5q31.2) candidate gene that may contribute to MDS and AML pathogenesis, respectively. To test whether HSPA9 haploinsufficiency recapitulates the features of ineffective hematopoiesis observed in MDS, we knocked down the expression of HSPA9 in primary human hematopoietic cells and in a murine bone marrow–transplantation model using lentivirally mediated gene silencing. Knockdown of HSPA9 in human cells significantly delayed the maturation of erythroid precursors, but not myeloid or megakaryocytic precursors, and suppressed cell growth by 6-fold secondary to an increase in apoptosis and a decrease in the cycling of cells compared with control cells. Erythroid precursors, B lymphocytes, and the bone marrow progenitors c-kit+/lineage−/Sca-1+ (KLS) and megakaryocyte/erythrocyte progenitor (MEP) were significantly reduced in a murine Hspa9-knockdown model. These abnormalities suggest that cooperating gene mutations are necessary for del(5q31.2) MDS cells to gain clonal dominance in the bone marrow. Our results demonstrate that Hspa9 haploinsufficiency alters the hematopoietic progenitor pool in mice and contributes to abnormal hematopoiesis.
Differential gene expression and clonal selection during cellular transformation induced by adhesion deprivation
Authors: Jinka Rajeswari , Kapoor Renu , Pavuluri Sivapriya , Raj Avinash T , Kumar Mahesh J , Rao Lakshmi , Pande Gopal 
Published: December 2010

Abstract

Background
Anchorage independent growth is an important hallmark of oncogenic transformation. Previous studies have shown that when adhesion dependent fibroblasts were prevented from adhering to a substrate they underwent anoikis. In the present study we have demonstrated how anoikis resistant cells gain the transformation related properties with sequential selection of genes. We have proposed this process as a model system for selection of transformed cells from normal cells.

Results
This report demonstrates that some fibroblasts can survive during late stages of anoikis, at which time they exhibit transformation-associated properties such as in vitro colony formation in soft agar and in vivo subcutaneous tumour formation in nude mice. Cytogenetic characterisation of these cells revealed that they contained a t (2; 2) derivative chromosome and they have a selective survival advantage in non adherent conditions. Gene expression profile indicated that these cells over expressed genes related to hypoxia, glycolysis and tumor suppression/metastasis which could be helpful in their retaining a transformed phenotype.

Conclusion
Our results reveal some new links between anoikis and cell transformation and they provide a reproducible model system which can potentially be useful to study multistage cancer and to identify new targets for drug development.
A novel web-based TinT application and the chronology of the Primate Alu retroposon activity
Authors: Churakov Gennady , Grundmann Norbert , Kuritzin Andrej , Brosius Jürgen , Makałowski Wojciech , Schmitz Jürgen 
Published: December 2010

Abstract

Background
DNA sequences afford access to the evolutionary pathways of life. Particularly mobile elements that constantly co-evolve in genomes encrypt recent and ancient information of their host's history. In mammals there is an extraordinarily abundant activity of mobile elements that occurs in a dynamic succession of active families, subfamilies, types, and subtypes of retroposed elements. The high frequency of retroposons in mammals implies that, by chance, such elements also insert into each other. While inactive elements are no longer able to retropose, active elements retropose by chance into other active and inactive elements. Thousands of such directional, element-in-element insertions are found in present-day genomes. To help analyze these events, we developed a computational algorithm (Transpositions in
Transpositions, or TinT) that examines the different frequencies of nested transpositions and reconstructs the chronological order of retroposon activities.

Results
By examining the different frequencies of such nested transpositions, the TinT application reconstructs the chronological order of retroposon activities. We use such activity patterns as a comparative tool to (1) delineate the historical rise and fall of retroposons and their relations to each other, (2) understand the retroposon-induced complexity of recent genomes, and (3) find selective informative homoplasy-free markers of phylogeny. The efficiency of the new application is demonstrated by applying it to dimeric Alu
Short INterspersed Elements (SINE) to derive a complete chronology of such elements in primates.

Conclusion
The user-friendly, web-based TinT interface presented here affords an easy, automated screening for nested transpositions from genome assemblies or trace data, assembles them in a frequency-matrix, and schematically displays their chronological activity history.
Massive parallel sequencing of mRNA in identification of unannotated salinity stress-inducible transcripts in rice (Oryza sativa L.)
Authors: Mizuno Hiroshi , Kawahara Yoshihiro , Sakai Hiroaki , Kanamori Hiroyuki , Wakimoto Hironobu , Yamagata Harumi , Oono Youko , Wu Jianzhong , Ikawa Hiroshi , Itoh Takeshi , Matsumoto Takashi 
Published: December 2010

Abstract

Background
Microarray technology is limited to monitoring the expression of previously annotated genes that have corresponding probes on the array. Computationally annotated genes have not fully been validated, because ESTs and full-length cDNAs cannot cover entire transcribed regions. Here, mRNA-Seq (an Illumina cDNA sequencing application) was used to monitor whole mRNAs of salinity stress-treated rice tissues.

Results
Thirty-six-base-pair reads from whole mRNAs were mapped to the rice genomic sequence: 72.0% to 75.2% were mapped uniquely to the genome, and 5.0% to 5.7% bridged exons. From the piling up of short reads mapped on the genome, a series of programs (Bowtie, TopHat, and Cufflinks) comprehensively predicted 51,301 (shoot) and 54,491 (root) transcripts, including 2,795 (shoot) and 3,082 (root) currently unannotated in the Rice Annotation Project database. Of these unannotated transcripts, 995 (shoot) and 1,052 (root) had ORFs similar to those encoding the amino acid sequences of functional proteins in a BLASTX search against UniProt and RefSeq databases. Among the unannotated genes, 213 (shoot) and 436 (root) were differentially expressed in response to salinity stress. Sequence-based and array-based measurements of the expression ratios of previously annotated genes were highly correlated.

Conclusion
Unannotated transcripts were identified on the basis of the piling up of mapped reads derived from mRNAs in rice. Some of these unannotated transcripts encoding putative functional proteins were expressed differentially in response to salinity stress.
Perturbation of the yeast N-acetyltransferase NatB induces elevation of protein phosphorylation levels
Authors: Helbig Andreas O , Rosati Sara , Pijnappel Pim WWM , van Breukelen Bas , Timmers Marc HTH , Mohammed Shabaz , Slijper Monique , Heck Albert JR 
Published: December 2010

Abstract

Background
The addition of an acetyl group to protein N-termini is a widespread co-translational modification. NatB is one of the main N-acetyltransferases that targets a subset of proteins possessing an N-terminal methionine, but so far only a handful of substrates have been reported. Using a yeast nat3Δ strain, deficient for the catalytic subunit of NatB, we employed a quantitative proteomics strategy to identify NatB substrates and to characterize downstream effects in nat3Δ.

Results
Comparing by proteomics WT and nat3Δ strains, using metabolic 15N isotope labeling, we confidently identified 59 NatB substrates, out of a total of 756 detected acetylated protein N-termini. We acquired in-depth proteome wide measurements of expression levels of about 2580 proteins. Most remarkably, NatB deletion led to a very significant change in protein phosphorylation.

Conclusions
Protein expression levels change only marginally in between WT and nat3Δ. A comparison of the detected NatB substrates with their orthologous revealed remarkably little conservation throughout the phylogenetic tree. We further present evidence of post-translational N-acetylation on protein variants at non-annotated N-termini. Moreover, analysis of downstream effects in nat3Δ revealed elevated protein phosphorylation levels whereby the kinase Snf1p is likely a key element in this process.
Evaluation of diversity among common beans (Phaseolus vulgaris L.) from two centers of domestication using 'omics' technologies
Authors: Mensack Meghan M , Fitzgerald Vanessa K , Ryan Elizabeth P , Lewis Matthew R , Thompson Henry J , Brick Mark A 
Published: December 2010

Abstract

Background
Genetic diversity among wild accessions and cultivars of common bean (Phaseolus vulgaris L.) has been characterized using plant morphology, seed protein allozymes, random amplified polymorphic DNA, restriction fragment length polymorphisms, DNA sequence analysis, chloroplast DNA, and microsatellite markers. Yet, little is known about whether these traits, which distinguish among genetically distinct types of common bean, can be evaluated using omics technologies.

Results
Three 'omics' approaches: transcriptomics, proteomics, and metabolomics were used to qualitatively evaluate the diversity of common bean from two Centers of Domestication (COD). All three approaches were able to classify common bean according to their COD using unsupervised analyses; these findings are consistent with the hypothesis that differences exist in gene transcription, protein expression, and synthesis and metabolism of small molecules among common bean cultivars representative of different COD. Metabolomic analyses of multiple cultivars within two common bean gene pools revealed cultivar differences in small molecules that were of sufficient magnitude to allow identification of unique cultivar fingerprints.

Conclusions
Given the high-throughput and low cost of each of these 'omics' platforms, significant opportunities exist for their use in the rapid identification of traits of agronomic and nutritional importance as well as to characterize genetic diversity.
Genome-wide binding of the orphan nuclear receptor TR4 suggests its general role in fundamental biological processes
Authors: O'Geen Henriette , Lin Yu-Hsuan , Xu Xiaoqin , Echipare Lorigail , Komashko Vitalina M , He Daniel , Frietze Seth , Tanabe Osamu , Shi Lihong , Sartor Maureen A , Engel James D , Farnham Peggy J 
Published: December 2010

Abstract

Background
The orphan nuclear receptor TR4 (human testicular receptor 4 or NR2C2) plays a pivotal role in a variety of biological and metabolic processes. With no known ligand and few known target genes, the mode of TR4 function was unclear.

Results
We report the first genome-wide identification and characterization of TR4 in vivo binding. Using chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq), we identified TR4 binding sites in 4 different human cell types and found that the majority of target genes were shared among different cells. TR4 target genes are involved in fundamental biological processes such as RNA metabolism and protein translation. In addition, we found that a subset of TR4 target genes exerts cell-type specific functions. Analysis of the TR4 binding sites revealed that less than 30% of the peaks from any of the cell types contained the DR1 motif previously derived from in vitro studies, suggesting that TR4 may be recruited to the genome via interaction with other proteins. A bioinformatics analysis of the TR4 binding sites predicted a cis regulatory module involving TR4 and ETS transcription factors. To test this prediction, we performed ChIP-seq for the ETS factor ELK4 and found that 30% of TR4 binding sites were also bound by ELK4. Motif analysis of the sites bound by both factors revealed a lack of the DR1 element, suggesting that TR4 binding at a subset of sites is facilitated through the ETS transcription factor ELK4. Further studies will be required to investigate the functional interdependence of these two factors.

Conclusions
Our data suggest that TR4 plays a pivotal role in fundamental biological processes across different cell types. In addition, the identification of cell type specific TR4 binding sites enables future studies of the pathways underlying TR4 action and its possible role in metabolic diseases.
SVM-based prediction of linear B-cell epitopes using Bayes Feature Extraction
Authors: Wee Lawrence JK , Simarmata Diane , Kam Yiu-Wing , Ng Lisa FP , Tong Joo Chuan 
Published: December 2010

Abstract

Backgound
The identification of B-cell epitopes on antigens has been a subject of intense research as the knowledge of these markers has great implications for the development of peptide-based diagnostics, therapeutics and vaccines. As experimental approaches are often laborious and time consuming, in silico methods for prediction of these immunogenic regions are critical. Such efforts, however, have been significantly hindered by high variability in the length and composition of the epitope sequences, making naïve modeling methods difficult to apply.

Results
We analyzed two benchmark datasets and found that linear B-cell epitopes possess distinctive residue conservation and position-specific residue propensities which could be exploited for epitope discrimination in silico. We developed a support vector machines (SVM) prediction model employing Bayes Feature Extraction to predict linear B-cell epitopes of diverse lengths (12- to 20-mers). The best SVM classifier achieved an accuracy of 74.50% and AROC of 0.84 on an independent test set and was shown to outperform existing linear B-cell epitope prediction algorithms. In addition, we applied our model to a dataset of antigenic proteins with experimentally-verified epitopes and found it to be generally effective for discriminating the epitopes from non-epitopes.

Conclusion
We developed a SVM prediction model utilizing Bayes Feature Extraction and showed that it was effective in discriminating epitopes from non-epitopes in benchmark datasets and annotated antigenic proteins. A web server for predicting linear B-cell epitopes was developed and is available, together with supplementary materials, at http://www.immunopred.org/bayesb/index.html.
Algorithms and semantic infrastructure for mutation impact extraction and grounding
Authors: Laurila Jonas B , Naderi Nona , Witte René , Riazanov Alexandre , Kouznetsov Alexandre , Baker Christopher JO 
Published: December 2010

Abstract

Background
Mutation impact extraction is a hitherto unaccomplished task in state of the art mutation extraction systems. Protein mutations and their impacts on protein properties are hidden in scientific literature, making them poorly accessible for protein engineers and inaccessible for phenotype-prediction systems that currently depend on manually curated genomic variation databases.

Results
We present the first rule-based approach for the extraction of mutation impacts on protein properties, categorizing their directionality as positive, negative or neutral. Furthermore protein and mutation mentions are grounded to their respective UniProtKB IDs and selected protein properties, namely protein functions to concepts found in the Gene Ontology. The extracted entities are populated to an OWL-DL Mutation Impact ontology facilitating complex querying for mutation impacts using SPARQL. We illustrate retrieval of proteins and mutant sequences for a given direction of impact on specific protein properties. Moreover we provide programmatic access to the data through semantic web services using the SADI (Semantic Automated Discovery and Integration) framework.

Conclusion
We address the problem of access to legacy mutation data in unstructured form through the creation of novel mutation impact extraction methods which are evaluated on a corpus of full-text articles on haloalkane dehalogenases, tagged by domain experts. Our approaches show state of the art levels of precision and recall for Mutation Grounding and respectable level of precision but lower recall for the task of Mutant-Impact relation extraction. The system is deployed using text mining and semantic web technologies with the goal of publishing to a broad spectrum of consumers.
TSCC: Two-Stage Combinatorial Clustering for virtual screening using protein-ligand interactions and physicochemical features
Authors: Clinciu Daniel L , Chen Yen-Fu , Ko Cheng-Neng , Lo Chi-Chun , Yang Jinn-Moon 
Published: December 2010

Abstract

Background
The increasing numbers of 3D compounds and protein complexes stored in databases contribute greatly to current advances in biotechnology, being employed in several pharmaceutical and industrial applications. However, screening and retrieving appropriate candidates as well as handling false positives presents a challenge for all post-screening analysis methods employed in retrieving therapeutic and industrial targets.

Results
Using the TSCC method, virtually screened compounds were clustered based on their protein-ligand interactions, followed by structure clustering employing physicochemical features, to retrieve the final compounds. Based on the protein-ligand interaction profile (first stage), docked compounds can be clustered into groups with distinct binding interactions. Structure clustering (second stage) grouped similar compounds obtained from the first stage into clusters of similar structures; the lowest energy compound from each cluster being selected as a final candidate.

Conclusion
By representing interactions at the atomic-level and including measures of interaction strength, better descriptions of protein-ligand interactions and a more specific analysis of virtual screening was achieved. The two-stage clustering approach enhanced our post-screening analysis resulting in accurate performances in clustering, mining and visualizing compound candidates, thus, improving virtual screening enrichment.
Improving protein secondary structure prediction based on short subsequences with local structure similarity
Authors: Lin Hsin-Nan , Sung Ting-Yi , Ho Shinn-Ying , Hsu Wen-Lian 
Published: December 2010

Abstract

Background
When characterizing the structural topology of proteins, protein secondary structure (PSS) plays an important role in analyzing and modeling protein structures because it represents the local conformation of amino acids into regular structures. Although PSS prediction has been studied for decades, the prediction accuracy reaches a bottleneck at around 80%, and further improvement is very difficult.

Results
In this paper, we present an improved dictionary-based PSS prediction method called SymPred, and a meta-predictor called SymPsiPred. We adopt the concept behind natural language processing techniques and propose synonymous words to capture local sequence similarities in a group of similar proteins. A synonymous word is an n- gram pattern of amino acids that reflects the sequence variation in a protein’s evolution. We generate a protein-dependent synonymous dictionary from a set of protein sequences for PSS prediction.
On a large non-redundant dataset of 8,297 protein chains (DsspNr-25), the average Q
3 of SymPred and SymPsiPred are 81.0% and 83.9% respectively. On the two latest independent test sets (EVA Set_1 and EVA_Set2), the average Q
3 of SymPred is 78.8% and 79.2% respectively. SymPred outperforms other existing methods by 1.4% to 5.4%. We study two factors that may affect the performance of SymPred and find that it is very sensitive to the number of proteins of both known and unknown structures. This finding implies that SymPred and SymPsiPred have the potential to achieve higher accuracy as the number of protein sequences in the NCBInr and PDB databases increases.

Conclusions
Our experiment results show that local similarities in protein sequences typically exhibit conserved structures, which can be used to improve the accuracy of secondary structure prediction. For the application of synonymous words, we demonstrate an example of a sequence alignment which is generated by the distribution of shared synonymous words of a pair of protein sequences. We can align the two sequences nearly perfectly which are very dissimilar at the sequence level but very similar at the structural level. The SymPred and SymPsiPred prediction servers are available at http://bio-cluster.iis.sinica.edu.tw/SymPred/.
UPS 2.0: unique probe selector for probe design and oligonucleotide microarrays at the pangenomic/ genomic level
Authors: Chen Shu-Hwa , Lo Chen-Zen , Su Sheng-Yao , Kuo Bao-Han , Hsiung Chao A , Lin Chung-Yen 
Published: December 2010

Abstract

Background
Nucleic acid hybridization is an extensively adopted principle in biomedical research, in which the performance of any hybridization-based method depends on the specificity of probes to their targets. To determine the optimal probe(s) for detecting target(s) from a sample cocktail, we developed a novel algorithm, which has been implemented into a web platform for probe designing. This probe design workflow is now upgraded to satisfy experiments that require a probe designing tool to take the increasing volume of sequence datasets.

Results
Algorithms and probe parameters applied in UPS 2.0 include GC content, the secondary structure, melting temperature (Tm), the stability of the probe-target duplex estimated by the thermodynamic model, sequence complexity, similarity of probes to non-target sequences, and other empirical parameters used in the laboratory. Several probe background options,
Unique probe within a group

,

Unique probe in a specific Unigene set

,

Unique probe based onthe pangenomic level

, and
Unique Probe in the user-defined genome/transcriptome

, are available to meet the scenarios that the experiments will be conducted. Parameters, such as salt concentration and the lower-bound Tm of probes, are available for users to optimize their probe design query. Output files are available for download on the result page. Probes designed by the UPS algorithm are suitable for generating microarrays, and the performance of UPS-designed probes has been validated by experiments.

Conclusions
The UPS 2.0 evaluates probe-to-target hybridization under a user-defined condition to ensure high-performance hybridization with minimal chance of non-specific binding at the pangenomic and genomic levels. The UPS algorithm mimics the target/non-target mixture in an experiment and is very useful in developing diagnostic kits and microarrays. The UPS 2.0 website has had more than 1,300 visits and 360,000 sequences performed the probe designing task in the last 30 months. It is freely accessible at http://array.iis.sinica.edu.tw/ups/.
Screen cast: http://array.iis.sinica.edu.tw/ups/demo/demo.htm