The problem of computing the reversal distance and determining a sequence of reversals to transform a genome in molecular biology is a powerful tool to derive relationships between genes. Given two signed permutations, we need to find the shortest sequence of reversals to transform one into another. The foremost polynomial-time algorithm to calculate the reversal distance used an overlap graph formed from the permutation to find connected components and then identified graph structures like hurdles. Previous researchers have used a Union-Find structure, an O(nα(n)) algorithm ( α->inverse Ackerman function) to determine the connected components. A linear time algorithm for finding the connected components, which was a faster implementation of the existing works was proposed later. This algorithm is applied to an unsigned extension of the signed permutation. In the first scan, cycles in a breakpoint graph were located. Then in a second scan, an overlap forest is formed which gave all the connected components of the permutation. In this paper, we optimize the existing algorithm to construct the overlap forest by reducing a scan of the unsigned permutation.
In this era of web, we have a huge amount of information overload over internet. To extract useful information, filtering is required. Search engines help to solve this problem to some extent but they do not provide personalization of data. Hence, there is a need of recommendation engine. With the help of recommender software the preferences of user for a particular product can be foreseen. Recommender systems help in pinpointing the required information thereby deescalating unwanted information. Collaborative filtering is the most efficient approach to create recommendations so that the identified choices of a user's group can be used to envisage the preferences for other users which are not yet known to them. Through this paper we endeavor to present a thorough survey of collaborative filtering methods that can help in future for further research in this field and thereby propose a solution to enhance the precision and recall measures of recommendations.
This chapter is a case study for presenting various modes of in-class lecture delivery, student-instructor interaction, and topic discussion. The aim of using numerous forms of teaching-learning pedagogy is for justifying and achieving the learning outcomes of the course. We have tried to incorporate and change strategies of having instructor-led training (ILT) materials to student-centric learning. It explores various learning styles and dimensions so that the course content may be delivered to its fullest. Adaptation of different types of learning styles is implemented to promote flexibility with the instructor and help the students perceive a topic in various flavours. The chapter also puts forth topic-wise teaching-learning pedagogy availed, students' motivations, as justified from their informal feedbacks, recommended actions that have a positive influence in topic delivery and understanding and usage in exploring the subject in relation to other domain studies. Blooms' cognitive level is also mentioned to give a concise idea of the topic depth that would be followed in this particular course delivery. The chapter also discusses the concept development and exploration, courserelated material design and development, and evaluation and analysis. The measurement framework is developed on the basis of the following criteria of intuitive capability levels, in-class response, topic understanding (based on student's informal and formal feedback), and marks-based evaluations. This inherently incorporates certain evaluation practices followed in this course. Having a high cohesion with bioinformatics, the course helps in offering computational solutions to sustainability-related issues. Further, based on NBA requirements, the course outcomes are also measured as per their given directives. Based on student's interactions, the course was found to be popular and useful to students. The computer science and engineering and information technology (CSE and IT) students could easily relate the understanding of data structures and algorithms captured in the interdisciplinary course, whereas the biotechnology students could relate their core knowledge in bioinformatics, genes, genetics, protein, and other domain knowledge to the various algorithms that can help in addressing solutions. The subject presents a win-win situation for students as they get to work in a domain with a vast dataset and that can have a huge impact on the human lifestyle and lifespan understanding.
Uterine leiomyosarcoma mimics leiomyoma of the uterus clinically and on ultrasound imaging. The clinical course and prognosis are however markedly different .The entity may commonly present as a pelvic recurrence after initial surgery for unsuspected leiomyosarcoma. The rarity of this clinical entity renders pre-operative diagnosis to be often missed. The staging of this uncommon variant is significantly influenced by the histopathologic diagnosis. Preoperative suspicion and relevant imaging is needed to improve diagnosis and thereby prognosis through proper surgical staging/sampling and optimal surgical resection as there are no specific tumour biomarkers yet. This is a case report depicting prospectively the outcome of a post-menopausal woman who underwent Total abdominal hysterectomy and bilateral salpingo-oophorectomy for a large fibroid which was confirmed histopathologically as Uterine Leiomyosarcoma( uLMS). After the histologic confirmation of uLMS, the patient was advised Combination chemotherapy, but she declined the adjuvant treatment. After 4 months of primary surgery with no initiation of Chemotherapy , she developed pelvic recurrence with invasion of bladder as detected by CT scan. The patient received 3 cycles of palliative combination Chemotherapy with Inj. Doxorubicin , Inj. Ifosfamide and Inj. Mesna ,Inj. Neukine after the detection of recurrence. She sadly succumbed a few days after completion of the third cycle of chemotherapy. This case report highlights the necessity to suspect the possibility of leiomyosarcoma in a post –menopausal lady with fibroid presenting for surgical management.
Bangladesh J Obstet Gynaecol, 2021; Vol. 36(1): 69-73
Determining graphic degree sequences and finding the spanning tree of a graph are two popular problems of combinatorial optimization. A simple graph that realizes such a degree sequence is often termed as a realization of the given sequence. In this paper we have proposed a method for generating a spanning tree from a degree sequence, provided the degree sequence is graphic and non-regular. The proposed method first constructs the adjacency matrix corresponding to the degree sequence and then applies a modified version of Prim's algorithm to generate the spanning tree from it.
Recognizing motifs in DNA sequences is a traditional conjunctional problem in the discipline of bioinformatics. Motif refers to the biologically functional short, recurring common sequence pattern in DNA strands involved in important processes taking place at the genetic level in an organism. Motif discovery is integral to problems such as antibody biomarker identification and transcription factor binding sites (TBFS) in the field of genetics and holds a greater importance to enable advances in understanding human genetics, biology and health. This problem has been comprehensively examined over the years but the complexity of most of the existing algorithms is still very high. This paper advocates an efficient methodology using some operations on the given sequences and tries to reduce the time and space complexity. The algorithm HMBMF illustrated in this paper is applicable for non-mutated motifs of known or unknown length collectively. The demonstrated algorithm uses hash-map to store all the suitable candidates and modified binary search is to find the pertinent motif. In this algorithm, a single DNA sequence is used to generate the possible suitable l-mers and stored in a hash map. The provided sequences are further iterated to narrow down the suitable l-mers. Finally, binary search is applied to ascertain the motif from the produced suitable candidates. The collective use of hash map and binary search results in an algorithm with comparatively low complexity. This algorithm can also be used for string matching and pattern detection etc.
A finite sequence of nonnegative integers is said to be graphical if there exists a finite simple graph, such that the degrees of its vertices corresponds to the terms of the sequence. Such a graph is often termed as a realization of the given degree sequence. In this paper we have proposed an algorithm that determines the realization of a given degree sequence by constructing the adjacency matrix from the given sequence. The input to the algorithm is a non-increasing sequence of positive integers. The output of the algorithm is the decision (graphic or non-graphic), along with the adjacency matrix, provided the sequence is graphical.
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