Added Papers

papers/_posts/2008-01-01-sample-align-d--a-high-performance-multiple-sequence-alignment-system-using-phylogenetic-sampling-and-domain-decomposition.md

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+---
+layout: paper
+title: "Sample-align-d: A high performance multiple sequence alignment system using phylogenetic sampling and domain decomposition"
+nickname: 2024-04-16-bottenhorn-salo-diva
+authors: "Saeed, Fahad; Khokhar, Ashfaq; "
+year: "2008"
+journal: IEEE
+volume: 
+issue:
+pages: 1-9
+is_published: True
+image: /assets/images/papers/biorxiv.png
+projects: []
+tags: []
+
+# Text
+fulltext:
+pdf:
+pdflink:
+pmcid:
+preprint: 
+supplement:
+
+# Links
+doi: "10.1109/IPDPS.2008.4536174"
+pmid:
+
+# Data and code
+github: [""]
+neurovault:
+openneuro: [""]
+figshare:
+figshare_names:
+osf:
+---
+{% include JB/setup %}
+
+# Abstract
+
+Multiple sequence alignment (MSA) is one of the most computationally intensive tasks in Computational Biology. Existing best known solutions for multiple sequence alignment take several hours (in some cases days) of computation time to align, for example, 2000 homologous sequences of average length 300. Inspired by the Sample Sort approach in parallel processing, in this paper we propose a highly scalable multiprocessor solution for the MSA problem in phylogenetically diverse sequences. Our method employs an intelligent scheme to partition the set of sequences into smaller subsets using k- mer count based similarity index, referred to as k-mer rank. Each subset is then independently aligned in parallel using any sequential approach. Further fine tuning of the local alignments is achieved using constraints derived from a global ancestor of the entire set. The proposed sample-align-D algorithm has been …

papers/_posts/2009-01-01-a-domain-decomposition-strategy-for-alignment-of-multiple-biological-sequences-on-multiprocessor-platforms.md

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+---
+layout: paper
+title: "A domain decomposition strategy for alignment of multiple biological sequences on multiprocessor platforms"
+nickname: 2024-04-16-bottenhorn-salo-diva
+authors: "Saeed, Fahad; Khokhar, Ashfaq; "
+year: "2009"
+journal: Academic Press
+volume: 69
+issue:
+pages: 666-677
+is_published: True
+image: /assets/images/papers/biorxiv.png
+projects: []
+tags: []
+
+# Text
+fulltext:
+pdf:
+pdflink:
+pmcid:
+preprint: 
+supplement:
+
+# Links
+doi: "10.1016/j.jpdc.2009.03.006"
+pmid:
+
+# Data and code
+github: [""]
+neurovault:
+openneuro: [""]
+figshare:
+figshare_names:
+osf:
+---
+{% include JB/setup %}
+
+# Abstract
+
+Multiple Sequences Alignment (MSA) of biological sequences is a fundamental problem in computational biology due to its critical significance in wide ranging applications including haplotype reconstruction, sequence homology, phylogenetic analysis, and prediction of evolutionary origins. The MSA problem is considered NP-hard and known heuristics for the problem do not scale well with increasing numbers of sequences. On the other hand, with the advent of a new breed of fast sequencing techniques it is now possible to generate thousands of sequences very quickly. For rapid sequence analysis, it is therefore desirable to develop fast MSA algorithms that scale well with an increase in the dataset size. In this paper, we present a novel domain decomposition based technique to solve the MSA problem on multiprocessing platforms. The domain decomposition based technique, in addition to yielding better …

papers/_posts/2009-01-01-an-overview-of-multiple-sequence-alignment-systems.md

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+---
+layout: paper
+title: "An Overview of Multiple Sequence Alignment Systems"
+nickname: 2024-04-16-bottenhorn-salo-diva
+authors: "Saeed, Fahad; Khokhar, Ashfaq; "
+year: "2009"
+journal: 
+volume: 
+issue:
+pages: 
+is_published: True
+image: /assets/images/papers/biorxiv.png
+projects: []
+tags: []
+
+# Text
+fulltext:
+pdf:
+pdflink:
+pmcid:
+preprint: 
+supplement:
+
+# Links
+doi: "10.48550/arXiv.0901.2747"
+pmid:
+
+# Data and code
+github: [""]
+neurovault:
+openneuro: [""]
+figshare:
+figshare_names:
+osf:
+---
+{% include JB/setup %}
+
+# Abstract
+
+An overview of current multiple alignment systems to date are described.The useful algorithms, the procedures adopted and their limitations are presented.We also present the quality of the alignments obtained and in which cases(kind of alignments, kind of sequences etc) the particular systems are useful.

papers/_posts/2009-01-01-multiple-sequence-alignment-system-for-pyrosequencing-reads.md

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+---
+layout: paper
+title: "Multiple sequence alignment system for pyrosequencing reads"
+nickname: 2024-04-16-bottenhorn-salo-diva
+authors: "Saeed, Fahad; Khokhar, Ashfaq; Zagordi, Osvaldo; Beerenwinkel, Niko; "
+year: "2009"
+journal: Springer Berlin Heidelberg
+volume: 
+issue:
+pages: 362-375
+is_published: True
+image: /assets/images/papers/biorxiv.png
+projects: []
+tags: []
+
+# Text
+fulltext:
+pdf:
+pdflink:
+pmcid:
+preprint: 
+supplement:
+
+# Links
+doi: "10.1007/978-3-642-00727-9_34"
+pmid:
+
+# Data and code
+github: [""]
+neurovault:
+openneuro: [""]
+figshare:
+figshare_names:
+osf:
+---
+{% include JB/setup %}
+
+# Abstract
+
+Pyrosequencing is among the emerging sequencing techniques, capable of generating upto 100,000 overlapping reads in a single run. This technique is much faster and cheaper than the existing state of the art sequencing technique such as Sanger. However, the reads generated by pyrosequencing are short in size and contain numerous errors. In order to use these reads for any subsequent analysis, the reads must be aligned . Existing multiple sequence alignment methods cannot be used as they do not take into account the specific positions of the sequences with respect to the genome, and are highly inefficient for large number of sequences. Therefore, the common practice has been to use either simple pairwise alignment despite its poor accuracy for error prone pyroreads, or use computationally expensive techniques based on sequential gap propagation. In this paper, we develop a …

papers/_posts/2009-01-01-pyro-align--sample-align-based-multiple-alignment-system-for-pyrosequencing-reads-of-large-number.md

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+---
+layout: paper
+title: "Pyro-align: Sample-align based multiple alignment system for pyrosequencing reads of large number"
+nickname: 2024-04-16-bottenhorn-salo-diva
+authors: "Saeed, Fahad; "
+year: "2009"
+journal: 
+volume: 
+issue:
+pages: 
+is_published: True
+image: /assets/images/papers/biorxiv.png
+projects: []
+tags: []
+
+# Text
+fulltext:
+pdf:
+pdflink:
+pmcid:
+preprint: 
+supplement:
+
+# Links
+doi: "10.48550/arXiv.0901.2751"
+pmid:
+
+# Data and code
+github: [""]
+neurovault:
+openneuro: [""]
+figshare:
+figshare_names:
+osf:
+---
+{% include JB/setup %}
+
+# Abstract
+
+Pyro-Align is a multiple alignment program specifically designed for pyrosequencing reads of huge number. Multiple sequence alignment is shown to be NP-hard and heuristics are designed for approximate solutions. Multiple sequence alignment of pyrosequenceing reads is complex mainly because of 2 factors. One being the huge number of reads, making the use of traditional heuristics,that scale very poorly for large number, unsuitable. The second reason is that the alignment cannot be performed arbitrarily, because the position of the reads with respect to the original genome is important and has to be taken into account.In this report we present a short description of the multiple alignment system for pyrosequencing reads.

papers/_posts/2010-01-01-a-graph-theoretic-framework-for-efficient-computation-of-hmm-based-motif-finder.md

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+---
+layout: paper
+title: "A graph-theoretic framework for efficient computation of HMM based motif finder"
+nickname: 2024-04-16-bottenhorn-salo-diva
+authors: "Saeed, Fahad; Burger, Lukas; Khokhar, Ashfaq; Zavolan, Mihaela; "
+year: "2010"
+journal: 
+volume: 
+issue:
+pages: 
+is_published: True
+image: /assets/images/papers/biorxiv.png
+projects: []
+tags: []
+
+# Text
+fulltext:
+pdf:
+pdflink:
+pmcid:
+preprint: 
+supplement:
+
+# Links
+doi: ""
+pmid:
+
+# Data and code
+github: [""]
+neurovault:
+openneuro: [""]
+figshare:
+figshare_names:
+osf:
+---
+{% include JB/setup %}
+
+# Abstract
+
+Understanding the mechanisms that regulate gene expression is a major challenge in computational biology. An important part of solution in understanding this problem is to identify the binding sites in DNA for transcription factors known as motifs. Discovery of motifs in unaligned sequences is a fundamental problem in computational biology. Motif search using HMM and gibbs sampling have been shown to be very effective in finding regulatory motifs. We recently proposed a novel motif finding algorithm [1] that models, within a general framework, binding elements in terms of a variable number of motifs that are separated by spacers of varying lengths. The model is very effective for motif finding, but is computationally very expensive. In this paper, we propose a graphtheoretic framework for efficient computation of our HMM model for motif finding. The proposed graph model is very flexible, easy to use and is shown …

papers/_posts/2010-01-01-high-performance-computational-biology-algorithms.md

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+---
+layout: paper
+title: "High performance computational biology algorithms"
+nickname: 2024-04-16-bottenhorn-salo-diva
+authors: "Saeed, Fahad; "
+year: "2010"
+journal: University of Illinois at Chicago
+volume: 
+issue:
+pages: 
+is_published: True
+image: /assets/images/papers/biorxiv.png
+projects: []
+tags: []
+
+# Text
+fulltext:
+pdf:
+pdflink:
+pmcid:
+preprint: 
+supplement:
+
+# Links
+doi: ""
+pmid:
+
+# Data and code
+github: [""]
+neurovault:
+openneuro: [""]
+figshare:
+figshare_names:
+osf:
+---
+{% include JB/setup %}
+
+# Abstract
+
+Multiple Sequence s Alignment (MSA) of biological sequences is a fundamental problem in computational biology due to its critical significance in wide ranging applications including haplotype reconstruction, sequence homology, phylogenetic analysis, and prediction of evolutionary origins. The MSA problem is considered NP-hard and known heuristics for the problem do not scale well with increasing number of sequences. On the other hand, with the advent of new breed of fast sequencing techniques it is now possible to generate thousands of sequences very quickly. For rapid sequence analysis, it is therefore desirable to develop fast MSA algorithms that scale well with the increase in the dataset size. In this dissertation, we propose a novel domain decomposition based technique to solve the multiple sequence alignment problem on multiprocessing platforms. The domain decomposition based technique, in …

papers/_posts/2010-01-01-parallel-algorithm-for-center-star-sequence-and-alignments-with-applications-to-short-reads.md

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+---
+layout: paper
+title: "Parallel Algorithm for Center Star Sequence and Alignments with Applications to Short Reads"
+nickname: 2024-04-16-bottenhorn-salo-diva
+authors: "Saeed, Fahad; Khokhar, Ashfaq; "
+year: "2010"
+journal: 
+volume: 
+issue:
+pages: 
+is_published: True
+image: /assets/images/papers/biorxiv.png
+projects: []
+tags: []
+
+# Text
+fulltext:
+pdf:
+pdflink:
+pmcid:
+preprint: 
+supplement:
+
+# Links
+doi: ""
+pmid:
+
+# Data and code
+github: [""]
+neurovault:
+openneuro: [""]
+figshare:
+figshare_names:
+osf:
+---
+{% include JB/setup %}
+
+# Abstract
+
+With the advent of fast sequencing techniques, such as 454 and Solexa, the number of sequences that need to be aligned and processed are reaching up to one billion sequences [1]. The alignment of these sequences with the reference genome is one of the basic steps in mapping, alignments, and sequence analysis related problems. Aligning of such a large number of sequences using traditional multiple sequence alignment algorithms is computationally infeasible. In this paper we present a highly scalable parallel algorithm to find the center star sequence and perform approximate alignments of such a large number of sequences. The proposed algorithm has been implemented on a cluster of workstations using MPI library, and experimental results to find the Center Sequence for up to 6.4 million sequences are presented. These results include detailed computation and communication complexity analysis as …

papers/_posts/2011-01-01-large‐scale-itraq‐based-quantification-of-phosphorylation-changes-during-vasopressin-signaling.md

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+---
+layout: paper
+title: "Large‐scale iTRAQ‐based quantification of phosphorylation changes during vasopressin signaling"
+nickname: 2024-04-16-bottenhorn-salo-diva
+authors: "Hoffert, Jason; Pisitkun, T; Saeed, F; Song, J; Knepper, M; "
+year: "2011"
+journal: Federation of American Societies for Experimental Biology
+volume: 
+issue:
+pages: 
+is_published: True
+image: /assets/images/papers/biorxiv.png
+projects: []
+tags: []
+
+# Text
+fulltext:
+pdf:
+pdflink:
+pmcid:
+preprint: 
+supplement:
+
+# Links
+doi: "10.1096/fasebj.25.1_supplement.1039.38"
+pmid:
+
+# Data and code
+github: [""]
+neurovault:
+openneuro: [""]
+figshare:
+figshare_names:
+osf:
+---
+{% include JB/setup %}
+
+# Abstract
+
+Protein phosphorylation plays a critical role in the signaling pathways regulating water transport in kidney collecting duct. A central mediator in this process is the hormone arginine vasopressin (AVP), which regulates phosphorylation of the water channel aquaporin‐2 (AQP2), although the exact mechanisms are not fully understood. Here we utilized a multiplexed, isotopic label‐based quantitative phosphoproteomic approach in order to explore the temporal dynamics of phosphorylation events triggered by vasopressin across multiple timepoints. Briefly, rat inner medullary collecting duct (IMCD) samples were incubated in the presence or absence of 1nM AVP for 0.5, 2, 5, and 15 min (n=3). Each sample was labeled with a different iTRAQ reagent, mixed and processed for shotgun phosphoproteomic analysis. Of the 12,533 phosphopeptides identified, 3,298 were found in at least 2 out of 3 time courses and had …