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San Jose State University

Faculty Publications, Computer Science

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Full-Text Articles in Biology

Draft Genome Sequences Of Three Monokaryotic Isolates Of The White-Rot Basidiomycete Fungus Dichomitus Squalens, Sara Casado López, Mao Peng, Paul Daly, Bill Andreopoulos, Jasmyn Pangilinan, Anna Lipzen, Robert Riley, Steven Ahrendt, Vivian Ng, Kerrie Barry, Chris Daum, Igor Grigoriev, Kristiina Hildén, Miia Mäkelä, Ronald De Vries May 2019

Draft Genome Sequences Of Three Monokaryotic Isolates Of The White-Rot Basidiomycete Fungus Dichomitus Squalens, Sara Casado López, Mao Peng, Paul Daly, Bill Andreopoulos, Jasmyn Pangilinan, Anna Lipzen, Robert Riley, Steven Ahrendt, Vivian Ng, Kerrie Barry, Chris Daum, Igor Grigoriev, Kristiina Hildén, Miia Mäkelä, Ronald De Vries

Faculty Publications, Computer Science

Here, we report the draft genome sequences of three isolates of the wood-decaying white-rot basidiomycete fungus Dichomitus squalens. The genomes of these monokaryons were sequenced to provide more information on the intraspecies genomic diversity of this fungus and were compared to the previously sequenced genome of D. squalens LYAD-421 SS1.


Efficient Unfolding Pattern Recognition In Single Molecule Force Spectroscopy Data, Bill Andreopoulos, Dirk Labudde Jun 2011

Efficient Unfolding Pattern Recognition In Single Molecule Force Spectroscopy Data, Bill Andreopoulos, Dirk Labudde

Faculty Publications, Computer Science

BackgroundSingle-molecule force spectroscopy (SMFS) is a technique that measures the force necessary to unfold a protein. SMFS experiments generate Force-Distance (F-D) curves. A statistical analysis of a set of F-D curves reveals different unfolding pathways. Information on protein structure, conformation, functional states, and inter- and intra-molecular interactions can be derived.ResultsIn the present work, we propose a pattern recognition algorithm and apply our algorithm to datasets from SMFS experiments on the membrane protein bacterioRhodopsin (bR). We discuss the unfolding pathways found in bR, which are characterised by main peaks and side peaks. A main peak is the result of the pairwise …


Unraveling Protein Networks With Power Graph Analysis, Loïc Royer, Matthias Reimann, Bill Andreopoulos, Michael Schroeder Jul 2008

Unraveling Protein Networks With Power Graph Analysis, Loïc Royer, Matthias Reimann, Bill Andreopoulos, Michael Schroeder

Faculty Publications, Computer Science

Networks play a crucial role in computational biology, yet their analysis and representation is still an open problem. Power Graph Analysis is a lossless transformation of biological networks into a compact, less redundant representation, exploiting the abundance of cliques and bicliques as elementary topological motifs. We demonstrate with five examples the advantages of Power Graph Analysis. Investigating protein-protein interaction networks, we show how the catalytic subunits of the casein kinase II complex are distinguishable from the regulatory subunits, how interaction profiles and sequence phylogeny of SH3 domains correlate, and how false positive interactions among high-throughput interactions are spotted. Additionally, we …