Sales Management Portal

Our project aim is to design a Sales Management Portal which is helpful for an organization to provide flexibility to interact with the users and clients. Current design is mainly focused on the manager user. In this project, we have provided the features like, 1. A search option: where manager user can track information of clients and all the users. Which was a major requirement. 2. Manager Console: Manager can create user accounts, can send messages and view details 3. Pipeline Reports: Manager can run various reports such as, List of prospects Reports of opportunities By date, by month, sales person This project reduces the time that takes to search for the clients, users in the database. All the users who uses this portal will get notified about the important information through notification option. This makes easy for the users prepare for the task after getting notified. And, also its beneficial to managers to intimate users by a single message. Manager can make notes related to the project. So, that he can check his important information that stored in the notes. This makes easy to manager that he cannot miss any information during the project deal. Manager can send messages to all the users by using message option. This makes easy to manager that he can convey his information by using message option. Manager can store all the information about the project and can export all the information to an excel file. This makes easy to send information through email to others. Manager can edit, view and delete information this makes manger to trash information which is not necessary or no use. This website does not replace any existing application or website. It’s completely a newly designed website

Translating nucleic acid binding protein function from model species to minor crops using transfer learning

Genomic elements such as proteins or genes are the basic unit of the genome and involved in the functioning of every biological process. Predicting, therefore, the function of these genomic elements is the first step in the understanding of functioning of plants under various stress conditions. To date, various types of computational methods have been developed to predict the function of a given protein sequence. The recent increase in the development of a number of methods has created its own set of problems leading to difficulty in applying on newly sequenced genomes especially non-model crops. Due to these reasons, the immediate requirement for development of sophisticated computational methods to predict the function of a given protein sequence is raised. This thesis presents three novel computational tools developed based on transfer learning algorithms to predict the function of a given protein sequence and these tools are: 1) TL-RBPPred, for prediction of RNA-binding proteins, outperformed SPOT-Seq, RNApred, RBPPred and BLASTp on HumanSet (AUC of 0.977), YeastSet (AUC of 0.971), ArabidopsisSet (AUC of 0.972) and GlymaxSet (AUC of 0.97); 2) TL-DBPPred, for prediction of DNA-binding proteins, outperformed DNABP, enDNA-Prot, iDNA-Prot, nDNAProt, iDNA-Prot|Dis, DNAbinder and BLASTp on an testing dataset (AUC of 0.988); and 3) TL-TFPred, for prediction of transcription factors, outperformed PlantTFcat, iTAK and BLASTp on testing dataset (AUC of 0.999) in terms of prediction accuracy. Further, both TL-RBPPred and TL-DBPPred were tested on the transcriptome of the non-model crop, Bambara groundnut (Vigna subterranea (L.) Verdc.), to identify RNA-binding and DNA-binding proteins, respectively. The results obtained from these tests indicated that these two methods outperformed in terms of prediction accuracy (AUC) as compared to existing current state-of-the art tools such as SPOT-Seq, RBPPred, iDNA-Prot and iDNA-Prot|Dis. Based on the performance, the developed methods will be useful in predicting the function of given protein sequences (DNA, RNA-binding and transcription factor) of model species as well as non-model crops

Comparison of Transient Elastography and Liver Biopsy in Assessing Fibrosis in Patients with Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) is a common cause of chronic liver disease. Ultrasound-based transient elastography (TE) or TE of the liver is a noninvasive tool for effectively evaluating liver stiffness and fibrosis. The study aimed to compare the accuracy of TE as assessed by Fibroscan with liver biopsy in staging fibrosis in patients with NAFLD. Consecutive NAFLD patients (N = 72) were prospectively enrolled. TE evaluation was performed with Fibroscan and compared with liver biopsy, which is a reference standard. Fibrosis was staged according to the METAVIR scoring system (Meta-analysis of Histological Data in Viral Hepatitis). TE scores and biopsy-related fibrosis stages were correlated. Diagnostic accuracy (sensitivity, specificity, positive and negative predictive values) of TE was evaluated. Data were analyzed using software R v3.6.3. Liver biopsy showed that 36.11% of patients did not exhibit fibrosis, whereas 25, 16.67, 15.28, and 6.94% of patients had stage F1 (portal/mild fibrosis), F2 (periportal/moderate fibrosis), F3 (bridging/severe fibrosis), and F4 (cirrhosis/advanced fibrosis), respectively. TE showed that 50% of patients had cirrhosis, whereas 20.83,15.28, and 13.86% of patients had mild, moderate, and severe fibrosis, respectively. TE had 71% accuracy, 89% sensitivity, and 38% specificity in diagnosing the severity of fibrosis. Hence, it can be implemented as a noninvasive alternative diagnostic tool for understanding the severity of fibrosis in patients with NAFLD. Moreover, it can also be used for quick early diagnosis of NAFLD, reliable staging of fibrosis, and understanding the need for liver transplantation in patients with NAFLD

The barley pan-genome reveals the hidden legacy of mutation breeding

Genetic diversity is key to crop improvement. Owing to pervasive genomic structural variation, a single reference genome assembly cannot capture the full complement of sequence diversity of a crop species (known as the ‘pan-genome’1). Multiple high-quality sequence assemblies are an indispensable component of a pan-genome infrastructure. Barley (Hordeum vulgare L.) is an important cereal crop with a long history of cultivation that is adapted to a wide range of agro-climatic conditions2. Here we report the construction of chromosome-scale sequence assemblies for the genotypes of 20 varieties of barley—comprising landraces, cultivars and a wild barley—that were selected as representatives of global barley diversity. We catalogued genomic presence/absence variants and explored the use of structural variants for quantitative genetic analysis through whole-genome shotgun sequencing of 300 gene bank accessions. We discovered abundant large inversion polymorphisms and analysed in detail two inversions that are frequently found in current elite barley germplasm; one is probably the product of mutation breeding and the other is tightly linked to a locus that is involved in the expansion of geographical range. This first-generation barley pan-genome makes previously hidden genetic variation accessible to genetic studies and breeding

Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis

Bambara groundnut (Vigna subterranea (L.) Verdc.) is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth and development of bambara groundnut, leading to losses in potential crop yield. Therefore, in this study we developed a computational pipeline to identify and analyze the genes and gene modules associated with low temperature stress responses in bambara groundnut using the cross-species microarray technique (as bambara groundnut has no microarray chip) coupled with network-based analysis. Analyses of the bambara groundnut transcriptome using cross-species gene expression data resulted in the identification of 375 and 659 differentially expressed genes (p<0.01) under the sub-optimal (23°C) and very sub-optimal (18°C) temperatures, respectively, of which 110 genes are commonly shared between the two stress conditions. The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. Modules of sub-optimal temperature stress are principally enriched with carbohydrate and lipid metabolic processes, while most of the modules of very sub-optimal temperature stress are significantly enriched with responses to stimuli and various metabolic processes. Several transcription factors (from MYB, NAC, WRKY, WHIRLY & GATA classes) that may regulate the downstream genes involved in response to stimulus in order for the plant to withstand very sub-optimal temperature stress were highlighted. The identified gene modules could be useful in breeding for low-temperature stress tolerant bambara groundnut varieties

Translating nucleic acid binding protein function from model species to minor crops using transfer learning

Genomic elements such as proteins or genes are the basic unit of the genome and involved in the functioning of every biological process. Predicting, therefore, the function of these genomic elements is the first step in the understanding of functioning of plants under various stress conditions. To date, various types of computational methods have been developed to predict the function of a given protein sequence. The recent increase in the development of a number of methods has created its own set of problems leading to difficulty in applying on newly sequenced genomes especially non-model crops. Due to these reasons, the immediate requirement for development of sophisticated computational methods to predict the function of a given protein sequence is raised. This thesis presents three novel computational tools developed based on transfer learning algorithms to predict the function of a given protein sequence and these tools are: 1) TL-RBPPred, for prediction of RNA-binding proteins, outperformed SPOT-Seq, RNApred, RBPPred and BLASTp on HumanSet (AUC of 0.977), YeastSet (AUC of 0.971), ArabidopsisSet (AUC of 0.972) and GlymaxSet (AUC of 0.97); 2) TL-DBPPred, for prediction of DNA-binding proteins, outperformed DNABP, enDNA-Prot, iDNA-Prot, nDNAProt, iDNA-Prot|Dis, DNAbinder and BLASTp on an testing dataset (AUC of 0.988); and 3) TL-TFPred, for prediction of transcription factors, outperformed PlantTFcat, iTAK and BLASTp on testing dataset (AUC of 0.999) in terms of prediction accuracy. Further, both TL-RBPPred and TL-DBPPred were tested on the transcriptome of the non-model crop, Bambara groundnut (Vigna subterranea (L.) Verdc.), to identify RNA-binding and DNA-binding proteins, respectively. The results obtained from these tests indicated that these two methods outperformed in terms of prediction accuracy (AUC) as compared to existing current state-of-the art tools such as SPOT-Seq, RBPPred, iDNA-Prot and iDNA-Prot|Dis. Based on the performance, the developed methods will be useful in predicting the function of given protein sequences (DNA, RNA-binding and transcription factor) of model species as well as non-model crops

Determination of Opinions Regarding Written Handover and Its Importance for Patient Safety: A Questionnaire-Based Study

Introduction: Handover is the communication of clinical information to support the transfer of patient care and is a major contributing factor to patient safety. Handovers can be provided verbally or in a written format. This study aimed to determine the opinions regarding written handover and its importance, postulating that it has a critical role in ensuring patient safety and has justification for implementation where not present. Materials and Methods: An observational online questionnaire comprising ten questions was sent to doctors at Luton and Dunstable University Hospital in September 2014. Answers to the questions were provided as free text or single row rating scale in a drop-down menu. The data were exported into SPSS to be analysed. Frequency and percentage of the answer choices were derived for each question. Results:The majority of respondents were physicians (51.3%). Those who had written handover stated that it was accurate with regards to patients’ clinical details (45%) and that inaccurate handover impedes quality of care and clinical management (61.7%). In cases where patient handover was not present, 28.3% of the respondents strongly agreed that handover could improve patient safety and staff familiarity with patients. Conclusion: The results suggest that written handover is a very powerful communication tool through which patient safety can be ensured, and its local and national implementation and maintenance are a possible logistical challenge. It is recommended to conduct further studies on this issue to determine its effectiveness once standardised and implemented within this study location, and at other care units