text: Dayhoff began a PhD in quantum chemistry under George Kimball in the Columbia University Department of Chemistry. In her graduate thesis, Dayhoff pioneered the use of computer capabilities – i.e. mass-data processing – to theoretical chemistry; specifically, she devised a method of applying punched-card business machines to calculate the resonance energies of several polycyclic organic molecules. Her management of her research data was so impressive that she was awarded a Watson Computing Laboratory Fellowship. As part of this award, she received access to "cutting-edge IBM electronic data processing equipment" at the lab.
  After completing her PhD, Dayhoff studied electrochemistry under Duncan A. MacInnes at the Rockefeller Institute from 1948 to 1951. In 1952, she moved to Maryland with her family and later received research fellowships from the University of Maryland (1957–1959), working on a model of chemical bonding with Ellis Lippincott. At Maryland, she gained her first exposure to a new high-speed computer, the IBM model 7094. After this ended, she joined the National Biomedical Research Foundation in 1960 as associate director (a position she held for 21 years). At the NBRF, she began to work with Robert Ledley, a dentist who had obtained a degree in physics and become interested in the possibilities of applying computational resources to biomedical problems. He had authored one of the earliest studies of biomedical computation, "Report on the Use of Computer in Biology and Medicine." With their combined expertise, they published a paper in 1962 entitled "COMPROTEIN: A computer program to aid primary protein structure determination" that described a "completed computer program for the IBM 7090" that aimed to convert peptide digests to protein chain data. They actually began this work in 1958, but were not able to start programming until late 1960.
  In the early 1960s, Dayhoff also collaborated with Ellis Lippincott and Carl Sagan to develop thermodynamic models of cosmo-chemical systems, including prebiological planetary atmospheres.  She developed a computer program that could calculate equilibrium concentrations of the gases in a planetary atmosphere, enabling the study of the atmospheres of Venus, Jupiter, and Mars, in addition to the present day atmosphere and the primordial terrestrial atmosphere. Using this program, she considered whether the primordial atmosphere had the conditions necessary to generate life. Although she found that numerous small biologically important compounds can appear with no special nonequilibrium mechanism to explain their presence, there were compounds necessary to life that were scarce in the equilibrium model (such as ribose, adenine, and cytosine).
  Dayhoff also taught physiology and biophysics at Georgetown University Medical Center for 13 years, served as a Fellow of the American Association for the Advancement of Science and was elected councillor of the International Society for the Study of the Origins of Life in 1980 after 8 years of membership. Dayhoff also served on the editorial boards of three journals: DNA, Journal of Molecular Evolution and Computers in Biology and Medicine.
  In 1966, Dayhoff pioneered the use of computers in comparing protein sequences and reconstructing their evolutionary histories from sequence alignments. To perform this work, she created the single-letter amino acid code to minimize the data file size for each sequence. This work, co-authored with Richard Eck, was the first application of computers to infer phylogenies from molecular sequences. It was the first reconstruction of a phylogeny (evolutionary tree) by computers from molecular sequences using a maximum parsimony method. In later years, she applied these methods to study a number of molecular relationships, such as the catalytic chain and bovine cyclic AMP-dependent protein kinase and the src gene product of Rous avian and Moloney murine sarcoma viruses; antithrombin-III, alpha-antitrypsin, and ovalbumin; epidermal growth factor and the light chain of coagulation factor X; and apolipoproteins A-I, A-II, C-I and C-III.
  Based on this work, Dayhoff and her coworkers developed a set of substitution matrices called the PAM (Percent Accepted Mutation), MDM (Mutation Data Matrix), or Dayhoff Matrix. They are derived from global alignments of closely related protein sequences. The identification number included with the matrix (ex. PAM40, PAM100) refers to the evolutionary distance; greater numbers correspond to greater distances. Matrices using greater evolutionary distances are extrapolated from those used for lesser ones. To produce a Dayhoff matrix, pairs of aligned amino acids in verified alignments are used to build a count matrix, which is then used to estimate at mutation matrix at 1 PAM (considered an evolutionary unit). From this mutation matrix, a Dayhoff scoring matrix may be constructed. Along with a model of indel events, alignments generated by these methods can be used in an iterative process to construct new count matrices until convergence.
  One of Dayhoffs most important contributions to bioinformatics was her Atlas of Protein Sequence and Structure, a book reporting all known protein sequences (totaling 65) that she published in 1965. This book published a degenerate encoding of amino acids. It was subsequently republished in several editions.  This led to the Protein Information Resource database of protein sequences, the first online database system that could be accessed by telephone line and available for interrogation by remote computers. The book has since been cited nearly 4,500 times. It and the parallel effort by Walter Goad which led to the GenBank database of nucleic acid sequences are the twin origins of the modern databases of molecular sequences.  The Atlas was organized by gene families, and she is regarded as a pioneer in their recognition. Frederick Sangers determination of the first complete amino acid sequence of a protein (insulin) in 1955, led a number of researchers to sequence various proteins from different species. In the early 1960s, a theory was developed that small differences between homologous protein sequences (sequences with a high likelihood of common ancestry) could indicate the process and rate of evolutionary change on the molecular level. The notion that such molecular analysis could help scientists decode evolutionary patterns in organisms was formalized in the published papers of Emile Zuckerkandl and Linus Pauling in 1962 and 1965.