A Two-Phase Dynamic Programming Algorithm Tool for DNA Sequences

Sequence alignment has to do with the arrangement of DNA, RNA, and protein sequences to identify areas of similarity. Technic ally, it involves the arrangement of the primary sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. Similarity may be a consequence of functional, s tructural, or evolutionary relationships between the sequences. If two sequences in an alignment share a common ancestor, mismatches can be interpreted as mutations, and gaps as insertions. Such information becomes of great use in vital areas such as the study of d iseases, genomics and generally in the biological sciences. Thus, sequence alignment presents not just an exciting field of study, but a field of great importance to mankind. In this light, we extensively studied about seventy (70) existing sequence alignment tools available to us. Most of these tools are not user friendly and cannot be used by biologists. The few tools that attempted both Local and Global algorithms are not ready available freely. We therefore implemented a sequence alignment tool (CU-Aligner) in an understandable, user-friendly and portable way, with click-of-a-button simplicity. This is done utilizing the Needleman-Wunsh and Smith-Waterman algorithms for global and local alignments, respectively which focuses primarily on DNA sequences. Our aligner is implemented in the Java language in both application and applet mode and has been efficient on all windows operating systems

HierarchyMap: A Novel Approach to Treemap Visualization of Hierarchical Data

The HierarchyMap describes a novel approach for Treemap Visualization method for representing large volume of hierarchical information on a 2-dimensional space. HierarchyMap algorithm is a new ordered treemap algorithm. Results of the implementation of HierarchyMap treemap algorithm show that it is capable of representing several thousands of hierarchical data on 2-dimensional space on a computer and Portable Device Application (PDA) screens while still maintaining the qualities found in existing treemap algorithms such as readability, low aspect ratio, reduced run time, and reduced number of thin rectangles. The HierarchyMap treemap algorithm is implemented in Java programming language and tested with dataset of Departmental and Faculty systems of Universities, Family trees, Plant and Animal taxonomy structure

Application of k Means Clustering algorithm for prediction of Students Academic Performance

The ability to monitor the progress of students academic performance is a critical issue to the academic community of higher learning. A system for analyzing students results based on cluster analysis and uses standard statistical algorithms to arrange their scores data according to the level of their performance is described. In this paper, we also implemented k mean clustering algorithm for analyzing students result data. The model was combined with the deterministic model to analyze the students results of a private Institution in Nigeria which is a good benchmark to monitor the progression of academic performance of students in higher Institution for the purpose of making an effective decision by the academic planners.Comment: IEEE format, International Journal of Computer Science and Information Security, IJCSIS January 2010, ISSN 1947 5500, http://sites.google.com/site/ijcsis

Reducing the Time Requirement of k-Means Algorithm

Traditional k-means and most k-means variants are still computationally expensive for large datasets, such as microarray data, which have large datasets with large dimension size d. In k-means clustering, we are given a set of n data points in ddimensional space Rd and an integer k. The problem is to determine a set of k points in Rd, called centers, so as to minimize the mean squared distance from each data point to its nearest center. In this work, we develop a novel k-means algorithm, which is simple but more efficient than the traditional k-means and the recent enhanced k-means. Our new algorithm is based on the recently established relationship between principal component analysis and the k-means clustering. We provided the correctness proof for this algorithm. Results obtained from testing the algorithm on three biological data and six non-biological data (three of these data are real, while the other three are simulated) also indicate that our algorithm is empirically faster than other known k-means algorithms. We assessed the quality of our algorithm clusters against the clusters of a known structure using the Hubert-Arabie Adjusted Rand index (ARIHA). We found that when k is close to d, the quality is good (ARIHA.0.8) and when k is not close to d, the quality of our new k-means algorithm is excellent (ARIHA.0.9). In this paper, emphases are on the reduction of the time requirement of the k-means algorithm and its application to microarray data due to the desire to create a tool for clustering and malaria research. However, the new clustering algorithm can be used for other clustering needs as long as an appropriate measure of distance between the centroids and the members is used. This has been demonstrated in this work on six non-biological data

The design and implementation of online medical record system (OMRS)

Access to appropriate and credible medical information is essential. It is however saddening that many developing countries, especially in sub-Saharan Africa, have low or no access to information on personal health status. The Online Medical Record System (OMRS) is a departure from the traditional paper-based medical record system of healthcare practices to an Internet based medical record storage system. In this paper, we implemented OMRS software that has successfully been able to store, update and modify the patients\' medical history records. It also creates an appointment scheduler system and a platform for online consultation. OMRS allows patients control their own records while allowing doctors access when they need it. OMRS provides a way for doctors and patients to replace thick medical charts and swap information without the need for costly and time-consuming office visits. The advent of internet has made it possible for OMRS to come up with a way in which the problem of computerizing medical records effectively and sharing it can be solved. The OMRS would serve important national interests and it is believed that implementation of the OMRS will have a dramatic impact on the overall quality of healthcare delivery in developing countrie

Computational identification of signalling pathways in Plasmodium falciparum

Malaria is one of the world’s most common and serious diseases causing death of about 3 million people each year. Its most severe occurrence is caused by the protozoan Plasmodium falciparum. Reports have shown that the resistance of the parasite to existing drugs is increasing. Therefore, there is a huge and urgent need to discover and validate new drug or vaccine targets to enable the development of new treatments for malaria. The ability to discover these drug or vaccine targets can only be enhanced from our deep understanding of the detailed biology of the parasite, for example how cells function and how proteins organize into modules such as metabolic, regulatory and signal transduction pathways. It has been noted that the knowledge of signalling transduction pathways in Plasmodium is fundamental to aid the design of new strategies against malaria. This work uses a linear-time algorithm for finding paths in a network under modified biologically motivated constraints. We predicted several important signalling transduction pathways in Plasmodium falciparum. We have predicted a viable signalling pathway characterized in terms of the genes responsible that may be the PfPKB pathway recently elucidated in Plasmodium falciparum. We obtained from the FIKK family, a signal transduction pathway that ends up on a chloroquine resistance marker protein, which indicates that interference with FIKK proteins might reverse Plasmodium falciparum from resistant to sensitive phenotype. We also proposed a hypothesis that showed the FIKK proteins in this pathway as enabling the resistance parasite to have a mechanism for releasing chloroquine (via an efflux process). Furthermore, we also predicted a signalling pathway that may have been responsible for signalling the start of the invasion process of Red Blood Cell (RBC) by the merozoites. It has been noted that the understanding of this pathway will give insight into the parasite virulence and will facilitate rational vaccine design against merozoites invasion. And we have a host of other predicted pathways, some of which have been used in this work to predict the functionality of some proteins

Design and Implementation of Text To Speech Conversion for Visually Impaired People

A Text-to-speech synthesizer is an application that converts text into spoken word, by analyzing and processing the text using Natural Language Processing (NLP) and then using Digital Signal Processing (DSP) technology to convert this processed text into synthesized speech representation of the text. Here, we developed a useful text-to-speech synthesizer in the form of a simple application that converts inputted text into synthesized speech and reads out to the user which can then be saved as an mp3.file. The development of a text to speech synthesizer will be of great help to people with visual impairment and make making through large volume of text easie

Application of Fizzy Logic in Decision Making on Student’s academic performance.

Decision making is a knowledge is a knowledge discovery in Fuzzy logic application. Therefore, this paper conceptually defined, explained, and implemented fuzzy logic to the model to system performance, specifically, students’ performance model is studied and the various results generated and the performance chart obtained from overall performance for each year for the consecutive eight years in making decisions for future academic performance are also obtained

Effect of Fermentation on Antinutritional Factors and in Vitro Protein Digestibility of Bambara Nut (Voandzeia subterranean L.)

Bambara nut (Voandzeia subterranean L.) has better nutritive values than most other legumes. However, it is being underutilized due to long cooking time, antinutritional constituents and dehulling constraints. Fermentation as a unit operation has been able to address most of the factors responsible for the underutilization of some legumes. In this study, a full factorial block design comprising of time (0, 12, 24, 36, 48, 60 and 72 h) and Rhizopus combinations (A, B, C, AB, AC, BC and ABC) were used. Three species of Rhizopus (R. oligosporus (A), R. oryzae (B) and R. nigricans (C)) and their combinations were used in the fermentation for 3 days. Fermented samples that were collected at 12 hourly intervals were blanched, dried and milled to Bambara Flour (BF).  The BF was evaluated for tannin, oxalate, phytate, trypsin inhibitors and in vitro protein digestibility (IVPD). The results show that fermentation significantly (p < 0.05) reduced the antinutritional factors and enhanced IVPD of bambara nut. Ranges of values for antinutritional factors were tannin (0.35 – 0.02), oxalate (1.54 – 0.39), phytate (35.20 – 10.70) and trypsin inhibitor (3.22 – 0.49mg/g) while in vitro protein digestibility were 21.70 – 66.14%. Therefore, fermented bambara nut flour could be useful to supplement starchy foods. Key words: Antinutritional factors, in vitro protein digestibility, Rhizopus, bambara flou